bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced Error Suppression for Accurate Detection of Low‐Frequency Variants
Authors: Chen Huimin , Yu Fei , Lu Debin , Huang Shiyue , Liu Songrui , Zhang Boseng , Shu Kunxian , Pu Dan 
Published: December 2024

ABSTRACTThe identification of low‐frequency variants remains challenging due to the inevitable high error rates of next‐generation sequencing (NGS). Numerous promising strategies employ unique molecular identifiers (UMIs) for error suppression. However, their efficiency depends highly on redundant sequencing and quality control, leading to tremendous read waste and cost inefficiency. Here, we describe a novel approach, enhanced error suppression strategy (EES), that addresses these challenges by (1) optimizing data utilization and reducing read waste by utilizing single‐read correction that reserves abundant single reads that complement other single reads or single‐strand consensus sequences (SSCSs), and (2) effectively enhancing the accuracy of NGS by employing Bayes’ theorem. EES significantly improves variant detection accuracy, achieving a background error rate of less than 4.4 × 10−5 per base pair. Additionally, the data utilization rate is dramatically increased, with a 22.9‐fold enhancement in duplex consensus sequence (DCS) recovery compared to traditional methodologies. Furthermore, EES demonstrates superior error suppression performance across various base substitutions. In conclusion, EES represents a significant advancement in detecting low‐frequency variants by improving data utilization and reducing sequencing errors. It potentially enhances the sensitivity and accuracy of NGS applications, proving highly valuable in clinical and research contexts where precise variant detection is critical.
Incidence and Predictors of Later Epilepsy in Neonates with Encephalopathy: The Impact of Electrographic Seizures
Authors: Stephens Carol M. , Proietti Jacopo , Mathieson Sean R. , Livingstone Vicki , McNamara Brian , McSweeney Niamh , O'Mahony Olivia , Walsh Brian H. , Murray Deirdre M. , Boylan Geraldine B. 
Published: December 2024

AbstractObjectivesTo determine the incidence of later epilepsy in full‐term infants with neonatal encephalopathy (NE) who undergo continuous electroencephalography (cEEG) monitoring in the neonatal period and to identify potential predictors of later epilepsy both in infants with and without electrographic neonatal seizures (ENS).MethodsThis was a retrospective observational study performed at Cork University Maternity Hospital, Cork, Ireland, between 2003 and 2019. All term infants with NE had a minimum of 2 h of cEEG monitoring in the neonatal period. ENS were identified via cEEG monitoring. Pediatric medical charts were reviewed to determine if epilepsy developed after the neonatal period and to determine potential predictors of epilepsy in infants both with and without ENS.ResultsTwo hundred and eighty infants were included. The overall incidence rate of epilepsy was 17.55 per 1000 person‐years (95% CI: 10.91 to 28.23). In infants with ENS (n = 82), the incidence rate was 39.27 per 1000 person‐years (95% CI: 22.30 to 69.16). In infants without ENS (n = 198), the incidence rate was 7.54 per 1000 person‐years (95% CI: 3.14 to 18.12). The incidence rate was significantly higher in the ENS group compared to the non‐ENS group (p‐value = 0.002). Several potential predictors for the development of later epilepsy were identified including infants delivered vaginally, low Apgar scores at 1 and 5 min, severe HIE diagnosis, presence of ENS, a severely abnormal EEG background and an abnormal brain MRI.SignificanceFollowing NE, term infants are at risk of epilepsy with a significantly higher incidence rate in infants who experience ENS compared to those who did not. Close follow‐up is required in both groups well into the childhood period.Plain Language SummaryThis study aimed to determine the occurrence of epilepsy in children who were monitored for seizures in the newborn period. The occurrence of epilepsy was higher in infants who experienced seizures in the newborn period compared to those who did not. Several potential predictors of later epilepsy were identified in both groups of infants (those with and without seizures in the newborn period). Both groups of infants require close follow‐up in childhood.
Numerical Study on the Effect of the Combined Radial Flow Field on the Performance of Proton Exchange Membrane Fuel Cells
Authors: Wu Weidong , Chen Yuan , Huang Zongming , Li Menghan , Liu Xiaori , Rao Zhonghao 
Published: December 2024

ABSTRACTAs the flow field structure has a crucial influence on the performance of the proton exchange membrane fuel cell, in this research, the radial flow field R‐0 is designed and optimized based on the characteristics of the annular serpentine and annular flow channels to form combined flow field structure (R‐1 to R‐5). Subsequently, a three‐dimensional and two‐phase model is established and the effects of each flow field on the cell performance are numerically investigated. Results indicate that the R‐0 can enhance the gas vertical velocity on the diffusion‐catalyst interface compared to the parallel flow field, which increases the effective concentration of reaction gases within the catalyst layer, thereby accelerating the electrochemical reaction rate, and the performance of the combined flow fields is further improved. In addition, the effect of the percentage of annular serpentine within the combined flow field on the concentration distribution, uniformity, and output performance is analyzed. Results indicate that increasing the percentage of annular serpentine structure can increase the pressure between adjacent channels, and thus the higher pressure and concentration gradient generated can enhance the gas transport and reduce the water accumulation under the ribs thus effectively improving the cell performance.
Pregnancy Entails a Metabolic Rewiring of Maternal Circulating Neutrophils
Authors: Calo Guillermina , Merech Fátima , Sabbione Florencia , Hauk Vanesa , Lara Brenda , Doga Luciana , D'eramo Luciana , Squassi Aldo , Ramhorst Rosanna , Trevani Analía , Vota Daiana , Leirós Claudia Pérez 
Published: December 2024

ABSTRACTImmunometabolism is an emerging growing field that focuses on the role of cellular metabolism in the regulation of immune cell function and fate. Thus, proliferation, differentiation, activation, and function of immune cell populations are modulated by reprogramming their fueling and metabolic pathways. Pregnancy entails a fine immune and metabolic regulation of the maternal−fetal interaction to assist the energetic demands of the fetus where trophoblast cells have a central role. Maternal neutrophil functional shaping by trophoblast cells has been proposed though their metabolic conditioning during pregnancy has not been studied yet. Here, we explored the effects of trophoblast‐derived factors on the metabolic rewiring of neutrophils from nonpregnant women and its impact on central functions like reactive oxygen species (ROS) production, neutrophil extracellular trap (NET) release, and migration. In parallel, the immunometabolic status and function of neutrophils isolated from pregnant women (16−20 weeks) was compared with nonpregnant age‐matched control samples. Trophoblast‐derived factors induced glucose uptake and lipid droplet accumulation without activating ROS production or NET release. Conditioned media from trophoblast cells also inhibited PMA‐induced NETosis partly by impairing glucose uptake in neutrophils. In turn, neutrophils from pregnant women had increased basal ROS production, lipid accumulation, and glucose uptake compared to neutrophils from nonpregnant women, accompanied by a higher release of PMA‐induced NETs. Interestingly, PMA‐induced NETs was blocked by a fatty acid oxidation inhibitor in neutrophils from pregnant women indicating the contribution of fatty acid metabolism to neutrophil activity during pregnancy. Results are consistent with immunometabolic mechanisms underlying the functional shaping of neutrophils during pregnancy and point out the contribution of trophoblast‐derived factors to their metabolic profiling. These findings provide novel immunometabolic clues to understand immune homeostasis maintenance during pregnancy and raise the clinical potential of monitoring neutrophil metabolism during normal and complicated pregnancies.
Enhanced Brain Tumor Classification Through Optimized Semantic Preserved Generative Adversarial Networks
Authors: Chaitanya Durbhakula M. K. , Aouthu Srilakshmi , Dhanalakshmi Narra , Srinivas Yerram , Dhanikonda Srinivasa Rao , Chinna Rao B. 
Published: December 2024

ABSTRACTBrain tumor is a most dangerous disease and requires accurate diagnosis in a short period to ensure the best treatment. Traditional methods for brain tumor classification (BTC) are quite effective, even though usually resulting in clinical manual analysis, which takes more time and prone to errors. Initially, the input image is collected from Brain Tumor dataset. The gathered image is given to preprocessing. In preprocessing stage, trust‐based distributed set‐membership filtering (TDSF) is used to remove the noise. The preprocessed output is fed to the quaternion offset linear canonical transform (QOLCT) for Grayscale statistic and Haralick texture features extraction. Then the extracted features are fed to the Semantic‐Preserved Generative Adversarial Network (SPGAN) for classifying the brain tumor into Glioma, Meningioma and Pituitary. Finally, Hunger Games Search Optimization (HGSO) is used to enhance the weight parameters of SPGAN. The proposed BTC‐SPGAN‐HGSO method attains the accuracies of 99.72% for Glioma, 99.65% for Meningioma, 99.52% for Pituitary and lowest MSE values across all tumor types, with 0.45% for Glioma, 0.39% for Meningioma, and 0.5% for Pituitary, which performs better than existing models. The simulation results highlight the effectiveness of the proposed BTC‐SPGAN‐HGSO approach in improving the accuracy of BTC and assist neurologists and physicians make exact decisions of diagnostic.
CD7‐targeting pro‐apoptotic extracellular vesicles: A novel approach for T‐cell haematological malignancy therapy
Authors: Zhang Bei , Chen Jianqiang , Chen Jiming , Shen Yingying , Chen Yinghu , Wang Shibo , Zhang Chengyan , He Yuzhou , Feng Huajun , Wang Jiaoli , Cai Zhijian 
Published: December 2024

AbstractT‐cell haematological malignancies progress rapidly and have a high mortality rate and effective treatments are still lacking. Here, we developed a drug delivery system utilizing 293T cell‐derived extracellular vesicles (EVs) modified with an anti‐CD7 single‐chain variable fragment (αCD7/EVs). Given the challenges of chemotherapy resistance in patients with T‐cell malignancy, we selected cytochrome C (CytC) and Bcl2 siRNA (siBcl2) as therapeutic agents and loaded them into αCD7/EVs (αCD7/EVs/CytC/siBcl2). We found that αCD7/EVs efficiently targeted and were internalized by human T‐ALL Molt‐4 cells. In addition, the interaction between αCD7 and CD7 switched the EV entry pathway in Molt‐4 cells from macropinocytosis‐dependent endocytosis to clathrin‐mediated endocytosis, thereby reducing EV‐lysosome colocalization, ultimately improving CytC delivery efficiency and increasing the cytotoxicity of nascent EVs from EV‐treated Molt‐4 cells. Notably, αCD7/EVs/CytC/siBcl2 demonstrated similar efficacy against both Molt‐4 and chemotherapy‐resistant Molt‐4 cells (CR‐Molt‐4). Furthermore, αCD7/EVs/CytC/siBcl2 exhibited high safety, low immunogenicity and minimal impact on human T cells. Therefore, αCD7/EVs/CytC/siBcl2 are promising therapeutic approaches for treating CD7+ T‐cell malignancies.
Machine Learning Methods Based on Limited Meteorological Data to Simulate Potential Evapotranspiration: A Case Study of Source Region of Yellow River Basin
Authors: Pei Yinan , Jian Shengqi , Zhang Guodong 
Published: December 2024

ABSTRACTSimulation of potential evapotranspiration (PET) is an important part of drought warning and water resource planning. However, the commonly used empirical models need to input a large number of meteorological elements. Therefore, to improve the efficiency and accuracy of PET simulation in areas lacking meteorological data, this study evaluated the performance of Extreme learning machine (ELM), multi‐layer perceptron (MLP), and Random Forest (RF) three machine learning methods to simulate daily PET using limited meteorological data in the source region of the Yellow River (SYRB). Two bionic optimization algorithms, Grey Wolf Optimizer (GWO) and Sparrow Search Algorithm (SSA), were used to optimise the hyperparameters of the model to improve the accuracy of the model. In addition, the effect of months on daily PET simulations was evaluated. The results showed that the daily maximum temperature (Tmax) was the most important factor affecting the PET simulation, and the daily average relative humidity (RH) and wind speed (U10) were the secondary factors. It is recommended to use Tmax, RH, U10, and sunshine duration as the optimum combination of input (R2 > 0.95). In the case of limited meteorological data, the input combination of Tmax, RH, U10, or Tmax, RH (R2 > 0.75) was considered. Considering the accuracy and the time and space overhead of the model, the ELM‐GWO model is recommended. When month information was used as an input factor, model performance improved in all scenarios, and June to July was the most accurate month for the model to simulate daily PET. This research resultwill allow researchers to choose the appropriate meteorological factor when simulating the PET to provide the reference.
Vertical nitrate flux fuels new production over summertime Northeast U.S. Shelf
Authors: Zheng Bofu , Zhang Weifeng (Gordon) , Ji Rubao , Stanley Rachel H. R. , Crockford E. Taylor , Fontaine Diana N. , Peacock Emily E. , Rynearson Tatiana A. , Sosik Heidi M. 
Published: December 2024

AbstractIn aquatic ecosystems, allochthonous nutrient transport to the euphotic zone is an important process that fuels new production. Here, we use high‐resolution physical and biogeochemical observations from five summers to estimate the mean vertical nitrate flux, and thus new production over the Northeast U.S. Shelf (NES). We find that the summertime nitrate field is primarily controlled by biological uptake and physical advection–diffusion processes, above and below the 1% light level depth, respectively. We estimate the vertical nitrate flux to be 8.2 ± 5.3 × 10−6 mmol N m−2 s−1 for the mid‐shelf and 12.6 ± 8.6 × 10−6 mmol N m−2 s−1 for the outer shelf. Furthermore, we show that the new production to total primary production ratio (i.e., the f‐ratio), consistently ranges between 10% and 15% under summer conditions on the NES. Two independent approaches—nitrate flux‐based new production and O2/Ar‐based net community production—corroborate the robustness of the f‐ratio estimation. Since ~ 85% of the total primary production is fueled by recycled nutrients over sufficiently broad spatial and temporal scales, less than 15% of the organic matter produced in summer is available for export from the NES euphotic zone. Our direct quantification of new production not only provides more precise details about key processes for NES food webs and ecosystem function, but also demonstrates the potential of this approach to be applied to other similar datasets to understand nutrient and carbon cycling in the global ocean.
Transparent Composite for Cooperative Near‐infrared and X‐ray Imaging
Authors: Huang Yupeng , Lv Shichao , Wang Dazhao , Dong Quan , Hou Dianhao , Chen Jingfei , Yu Zhuoming , Jiang Quan , Li Xueliang , Wu YuanKui , Qiu Jianrong , Zhou Shifeng 
Published: December 2024

AbstractThe advancement of imaging technology has significantly contributed to the progress in medical diagnosis and treatment, biomedical science, and various other fields. However, the visualization of comprehensive information on the imaged target remains a great challenge, especially for the complex biological system. Herein, it is proposed that the Cr3+‐doped transparent glass composite with near‐infrared (NIR) activity may gift a new possibility for achieving cooperative imaging. It presents remarkable photoluminescence (PL) and radioluminescence (RL) response in the NIR region, with ultra‐broadband tunable luminescence (full‐width half‐maximum from 47 to 263 nm), excellent external quantum efficiency (>50%), and robust RL thermal quenching resistance (83.85%@150 °C). Benefiting from these distinctive features, NIR imaging and high‐resolution X‐ray imaging with a spatial resolution exceeding 19 lp mm−1 are successfully realized. Furthermore, a cooperative imaging device is developed and its practical applications for simultaneously visualizing bone and blood vessels in biological targets are demonstrated. These findings represent a significant advancement in the field of NIR active photonic materials for cutting‐edge imaging technology.
Urban Green Innovation and the Export of Low‐Carbon Products by Firms in Emerging Markets: Evidence From Chinese Manufacturing Firms
Authors: Gao Qiang , Song Lin , Hu Chen‐Xi , Shi Beibei 
Published: December 2024

ABSTRACTGiven the backdrop of global warming and the rise of more stringent green trade barriers, such as the Carbon Border Adjustment Mechanism, we utilize data from firms in the world's largest emerging market to theoretically analyze and empirically test the effects of urban green innovation on the export of low‐carbon products by firms. First, urban green innovation significantly boosts the export of low‐carbon products by firms. Second, our analysis of the mechanisms shows that urban green innovation enhances firms' export of low‐carbon products by lowering production costs, easing internal financing constraints, and helping them navigate green trade barriers in host countries. Third, urban green innovation contributes simultaneously to reducing firms' energy consumption and pollution emissions, and it plays a significant role in expanding the export variety of low‐carbon products by firms, as well as increasing the number of host countries they serve. Our heterogeneity analysis reveals that the more differentiated the low‐carbon products, the greater the impact of urban green innovation. Moreover, urban green innovation has a more significant effect on promoting the export of low‐carbon products by non–state‐owned firms compared to state‐owned ones.
High‐Q LNA With a VCO for Small Calibration Frequency Errors
Authors: Lee Gyeong‐Seok , Huynh Phuoc B. T. , Park Jun‐Young , Yun Tae‐Yeoul 
Published: December 2024

ABSTRACTA high‐quality (Q) low‐noise amplifier (LNA) combined with a voltage‐controlled oscillator (VCO) is presented for small frequency errors in self‐calibration. The proposed new double capacitive‐cross‐coupled structure controls negative impedance and thus, changes the working mode between the LNA and VCO with a small variation of parasitic capacitance, which results in a small calibration frequency error. High‐Q and low‐noise performances were theoretically analyzed and confirmed by simulation and measurement. The measured LNA operated from 2.2 to 2.44 GHz with a Q‐factor of 34 while the frequency offset was less than 0.9%. A power gain of 27 dB, noise figure of 2.1 dB, and input third‐order intercept point (IIP3) of −17 dBm were obtained while the power dissipations of the LNA and VCO modes were 10.2 and 4.7 mW from a 1.5‐V supply, respectively.
Deuterium Metabolic Imaging Enables the Tracing of Substrate Fluxes Through the Tricarboxylic Acid Cycle in the Liver
Authors: Ehret Viktoria , Dürr Sabine C. , Ustsinau Usevalad , Friske Joachim , Scherer Thomas , Fürnsinn Clemens , Starčuková Jana , Helbich Thomas H. , Philippe Cécile , Krššák Martin 
Published: December 2024

ABSTRACTAlterations in tricarboxylic acid (TCA) cycle metabolism are associated with hepatic metabolic disorders. Elevated hepatic acetate concentrations, often attributed to high caloric intake, are recognized as a pivotal factor in the etiology of obesity and metabolic syndrome. Therefore, the assessment of acetate breakdown and TCA cycle activity plays a central role in understanding the impact of diet‐induced alterations on liver metabolism. Magnetic resonance‐based deuterium metabolic imaging (DMI) could help to unravel the underlying mechanisms involved in disease development and progression, however, the application of conventional deuterated glucose does not lead to substantial enrichment in hepatic glutamine and glutamate. This study aimed to demonstrate the feasibility of DMI for tracking deuterated acetate breakdown via the TCA cycle in lean and diet‐induced fatty liver (FL) rats using 3D DMI after an intraperitoneal infusion of sodium acetate‐d3 at 9.4T. Localized and nonlocalized liver spectra acquired at 10 time points post‐injection over a 130‐min study revealed similar intrahepatic acetate uptake in both animal groups (AUCFL = 717.9 ± 131.1 mM▯min−1, AUClean = 605.1 ± 119.9 mM▯min−1, p = 0.62). Metabolic breakdown could be observed in both groups with an emerging glutamine/glutamate (Glx) peak as a downstream metabolic product (AUCFL = 113.6 ± 23.8 mM▯min−1, AUClean = 136.7 ± 41.7 mM▯min−1, p = 0.68).This study showed the viability of DMI for tracking substrate flux through the TCA cycle, underscoring its methodological potential for imaging metabolic processes in the body.
Partnership With Patient Advocacy Organizations Improves Research Recruitment
Authors: Wiener Lori , Buff Kimberly , Canter Kimberly , Pariseau Emily , Scialla Michele A. , Brown Victoria Sardi , Kazak Anne E. 
Published: December 2024

ABSTRACTIncorporating and elevating the voices of patients and families is of utmost importance in pediatric psychosocial research. While recognized as a priority, this practice is not commonplace, and specific guidance regarding best practices and procedures is largely absent. This paper describes partnering equitably with pediatric oncology patient advocacy groups to conduct the Implementing the Standards Together: Engaging Parents and Providers in Psychosocial Care (iSTEPPP) study. The partnership was critical for all steps of the research process, including study development, refinement of the survey instrument, and recruitment procedures. We describe our overall approach, providing specific illustrative examples and highlighting opportunities for future growth.
Possibilities of Application of Cold Atmospheric Pressure Plasmas in Dentistry—A Narrative Review
Authors: Banaszak Angelika , Terefinko Dominik , Motyka‐Pomagruk Agata , Grzebieluch Wojciech , Wdowiak Justyna , Pohl Pawel , Sledz Wojciech , Malicka Barbara , Jamroz Piotr , Skoskiewicz‐Malinowska Katarzyna , Dzimitrowicz Anna 
Published: December 2024

ABSTRACTAccording to the World Human Organization (WHO), dental and periodontal diseases are common among the human population. Traditional dentistry offers a wide range of methods for treating oral diseases and performing esthetic procedures. In contrast, cold atmospheric pressure plasma (CAPP) has been found to be a promising technology in multiple fields, particularly in medical sciences such as dentistry. In this study, CAPP might be a promising adjunct to conventional dental treatments. A substantial number of studies have confirmed the effectiveness of both direct and indirect CAPP applications in dentistry. Because CAPP technology is fast, inexpensive, and noninvasive, we aim to review recent literature focused on the application of this methodology in dentistry.