bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hepatocyte‐Targeted Lipid Nanoparticle Delivery of HERC2 Plasmid Controls Drug‐Induced Hepatotoxicity by Limiting β‐Catenin‐Regulated CYP2E1 Expression
Authors: Liu Yunzhi , Xu Qishan , Liu Yan , Cao Sihang , Luo Jialiang , Zheng Zhuojun , Zhou Jia , Lu Xiao , Zhang Liyun , Tan Yanan , Chen Qingyun , Zuo Daming 
Published: October 2024

AbstractUnderstanding the molecular mechanisms that bridge hepatic inflammation and liver injury is crucial for developing effective therapeutic strategies for drug‐induced liver injury (DILI) management. HECT domain and RCC1‐like domain 2 (HERC2) belongs to the large Herc family of ubiquitin E3 ligases, which are implicated in tissue development and inflammation. The observation reveals a pronounced HERC2 expression in specific hepatocyte subsets that proliferate in response to DILI in humans, prompting an investigation into the role of HERC2 in distinct DILI progression. Under the APAP challenge, liver‐specific HERC2‐deficient mice suffer more severe liver damage. Integrated single‐cell RNA sequencing analysis unveils a negative correlation between HERC2 and CYP2E1, a vital metabolic enzyme for xenobiotics, in hepatocytes from APAP‐challenged mice. Mechanistically, HERC2 interacts with β‐catenin to promote its ubiquitination, thereby governing CYP2E1 transcriptional regulation. Targeted hepatic delivery of lipid nanoparticle‐encapsulated HERC2‐overexpressing plasmid markedly reduces liver damage caused by APAP overdose. Collectively, these findings elucidate a previously unrecognized protective role of HERC2 in protecting against acute liver injury associated with drug metabolism disorders, highlighting its potential as a therapeutic target in treating DILI.
In Vivo Assessment of Deep Vascular Patterns in Murine Colitis Using Optoacoustic Mesoscopic Imaging
Authors: Buehler Adrian , Brown Emma L. , Nedoschill Emmanuel , Eckstein Markus , Ludwig Petra , Wachter Felix , Mandelbaum Henriette , Raming Roman , Oraiopoulou Mariam‐Eleni , Paulus Lars‐Philip , Rother Ulrich , Friedrich Oliver , Neurath Markus F. , Woelfle Joachim , Waldner Maximilian J. , Knieling Ferdinand , Bohndiek Sarah E. , Regensburger Adrian P. 
Published: October 2024

AbstractThe analysis of vascular morphology and functionality enables the assessment of disease activity and therapeutic effects in various pathologies. Raster‐scanning optoacoustic mesoscopy (RSOM) is an imaging modality that enables the visualization of superficial vascular networks in vivo. In murine models of colitis, deep vascular networks in the colon wall can be visualized by transrectal absorber guide raster‐scanning optoacoustic mesoscopy (TAG‐RSOM). In order to accelerate the implementation of this technology in translational studies of inflammatory bowel disease, an image‐processing pipeline for TAG‐RSOM data has been developed. Using optoacoustic data from a murine model of chemically‐induced colitis, different image segmentation methods are compared for visualization and quantification of deep vascular patterns in terms of vascular network length and complexity, blood volume, and vessel diameter. The presented image‐processing pipeline for TAG‐RSOM enables label‐free in vivo assessment of changes in the vascular network in murine colitis with broad applications for inflammatory bowel disease research.
Spatio‐Selective Reconfiguration of Mechanical Metamaterials Through the Use of Dynamic Covalent Chemistries
Authors: Abbasoglu Tansu , Skarsetz Oliver , Fanlo Paula , Grignard Bruno , Detrembleur Christophe , Walther Andreas , Sardon Haritz 
Published: October 2024

AbstractMechanical metamaterials achieve unprecedented mechanical properties through their periodically interconnected unit cell structure. However, their geometrical design and resulting mechanical properties are typically fixed during fabrication. Despite efforts to implement covalent adaptable networks (CANs) into metamaterials for permanent shape reconfigurability, emphasis is given to global rather than local shape reconfiguration. Furthermore, the change of effective material properties like Poisson's ratio remains to be explored. In this work, a non‐isocyanate polyurethane elastomeric CAN, which can be thermally reconfigured, is introduced into a metamaterial architecture. Structural reconfiguration allows for the local and global reprogramming of the Poisson's ratio with change of unit cell angle from 60° to 90° for the auxetic and 120° to 90° for the honeycomb metamaterial. The respective Poisson's ratio changes from −1.4 up to −0.4 for the auxetic and from +0.7 to +0.2 for the honeycomb metamaterial. Carbon nanotubes are deposited on the metamaterials to enable global and spatial electrothermal heating for on‐demand reshaping with a heterogeneous Poisson's ratio ranging from −2 to ≈0 for a single auxetic or +0.6 to ≈0 for a single honeycomb metamaterial. Finite element simulations reveal how permanent geometrical reconfiguration results from locally and globally relaxed heated patterns.
Quantifying Efficiency Roll‐Off Factors in Quantum‐Dot Light‐Emitting Diodes
Authors: Yan Xianchang , Zhu Xitong , Wu Boning , Jin Yizheng , Tian Wenming , Jin Shengye 
Published: October 2024

AbstractThe application of quantum‐dot light‐emitting diodes (QLEDs) is hindered by efficiency roll‐off at high current densities. Factors contributing to this roll‐off include Auger recombination, electric field‐induced quenching, Joule heating, and electron leakage into the hole transport layer. However, a method to quantitatively attribute the contribution of each factor to roll‐off has not yet been available, leaving the primary cause of roll‐off unidentified. This work addresses this gap using electrically pumped transient absorption spectroscopy, which measures the accumulated electrons and electric field in quantum dots (QDs). This study also introduces a method to quantify electron leakage in QLEDs using this spectroscopic technique. Based on the spectroscopic experimental results, the contribution of each factor to roll‐off is quantified. A green QLED with a peak external quantum efficiency (EQE) of 26.8% is studied as an example. The EQE declines to 20.5% at a current density of 354 mA cm−2, where field‐induced quenching accounts for 5% of the efficiency roll‐off, and electron leakage contributes 95%. Contributions from Auger recombination and heat‐induced quenching are negligible. This work demonstrates strong correlations between roll‐off and electron leakage amplitude using statistical data obtained in multiple QLEDs, confirming that electron leakage is the primary factor in EQE roll‐off.
UV‐Triggered In Situ Formation of a Robust SEI on Black Phosphorus for Advanced Energy Storage: Boosting Efficiency and Safety via Rapid Charge Integration Plasticity
Authors: Wang Qingxiang , Liu Fusheng , Qi Zhenguo , Qin Guohui , Wang Li , He Xiangming 
Published: October 2024

AbstractBlack phosphorus (BP) emerges as a highly promising electrode material for next generation of energy‐storage systems. Yet, its full potential is hindered by the instability of the solid‐electrolyte interphase (SEI) and the inflammability of its liquid systems. Here a pioneering UV‐induced in situ strategy is introduced for SEI construction, which leverages rapid electron supply to fracture sulfur‐dihalide bonds. This technique yields internal dihalide inorganic components and an external polymer segment, with any excess organic material being purged through pores. The (E)‐2‐chloro‐4‐((3′‐chloro‐4′‐hydroxyphenyl)diazinyl)phenyl acrylate (CA), with chlorine‐terminated groups, is initially in situ transformed into a flame‐retardant phenyl carboxylic acid (PCA), and then encapsulated within an ultrathin BP nanostructure, further nested in nitrogen (N), boron (B) co‐doped carbon (C) sheets that accommodate cobalt (Co) single atoms/nanoclusters (Co‐NBC). The Co‐NBC@BP@PCA construct demonstrates an impressive initial Coulombic efficiency (ICE) of 99.1% and maintains exceptional stabilities in terms of mechanical, chemical, and electrochemical performancecritical for prolonged cycle and calendar life. This research sheds light on the interplay between the rapid charge supply integrated in situ plasticity (RSIP) approach and the proactive establishment of an artificial SEI layer, offering profound insights into enhancing the durability and providing a solid foundation for advancements in energy storage technology.
Processing‐induced reduction in dianthrones content and toxicity of Polygonum multiflorum: Insights from ultra‐high performance liquid chromatography triple quadrupole mass spectrometry analysis and toxicological assessment
Authors: Li Wan‐Fang , Wang Ying , Qiu Cai‐Xia , Li Jie , Bao Jie , Yang Jian‐Bo , Jin Hong‐Tao 
Published: October 2024

AbstractBackgroundPolygonum multiflorum‐induced liver injury (PM‐DILI) has significantly hindered its clinical application and development.MethodsThis study investigates the variation in content and toxicity of dianthrones, the toxic components of P. multiflorum, during different processing cycles. We employed the ultra‐high‐performance liquid chromatography triple quadrupole mass spectrometry method to quantify six dianthrones in raw P. multiflorum and formulations processed with a method called nine cycles of steaming and sunning. Additionally, toxicity assessments were conducted using human normal liver cell line L02 and zebrafish embryos.ResultsResults indicate a gradual reduction in dianthrones content with increasing processing cycles. Processed formulations exhibited significantly reduced cytotoxicity in L02 cells and hepatotoxicity in zebrafish embryos.ConclusionsOur findings elucidate the relationship between processing cycles and P. multiflorum toxicity, providing theoretical support for its safe use.
Influence of wettability and surface tension on bubble formation from a needle
Authors: Jia Meng , Pang Mingjun 
Published: October 2024

AbstractThe multiphase flow accompanied by contact line motion is a common flow phenomenon in nature and industry. When investigating the bubble formation from a needle, it is generally assumed that the contact line is fixed at the inner diameter of a needle. Namely, the influence of contact line motion on bubble formation is ignored. In this paper, the effects of wettability and surface tension on the characteristics of bubble formation were studied using volume of fluid method. The changes of bubble volume, instantaneous contact angle, contact line radius, and the motion mechanism of contact line were analyzed in detail. It is found that when surface wettability and/or surface tension are different, the motion type of contact line during bubble formation is different, and the stage of bubble formation shows a great difference too. The motion of contact line is mainly affected by the pressure inside a bubble, the adhesion force, and the hydrostatic pressure of liquid outside a bubble. The sum of all forces driving contact line to move inward or outward controls the motion type of contact line.
Arrangements of intramembranous muscles of wings are influenced by body mass across the radiation of phyllostomid bats
Authors: Conceição‐da‐Silva Alana , Louzada Nathália Siqueira Veríssimo , Tavares William Corrêa 
Published: October 2024

AbstractExtensive research into bat flight mechanisms has highlighted the complex functional and evolutionary dynamics of their wing structures, yet the anatomical details of certain wing muscles remain elusive. In particular, the intramembranous plagiopatagiales proprii muscles, located within the plagiopatagium—an area of the wing lacking direct joint connections—exhibit remarkable variation across bat families. These muscles, which extend anteroposteriorly in macroscopic bundles, play a crucial role in wing stiffening, modulating membrane tension, and reducing wing curvature during flight. Since larger bats tend to have higher wing loading (WL; the ratio of body mass [BMa] to wing area) and may therefore experience increased patagial curvature and resultant drag, we hypothesized that body size significantly influences the evolutionary development of the plagiopatagiales proprii muscles. This study investigates the relationship between BMa and the morphology of the plagiopatagiales proprii in New World leaf‐nosed bats (Phyllostomidae), employing bivariate allometry, multivariate analysis, and comparative phylogenetic methods across 24 species from eight phyllostomid subfamilies. Our findings reveal a significant phylogenetic signal in muscle architecture, along with positive evolutionary allometry in muscle area. This suggests an adaptive increase in muscle size in larger species, likely to counterbalance the increased WL, reduce wing curvature, and minimize drag. This research enhances our understanding of the functional and adaptive morphological evolution of intramembranous wing muscles in phyllostomid bats, underscoring their evolutionary significance.
New Anti‐Angiogenic Therapy for Glioblastoma With the Anti‐Depressant Sertraline
Authors: Tsuboi Nobushige , Otani Yoshihiro , Uneda Atsuhito , Ishida Joji , Suruga Yasuki , Matsumoto Yuji , Fujimura Atsushi , Fujii Kentaro , Matsui Hideki , Kurozumi Kazuhiko , Date Isao , Michiue Hiroyuki 
Published: October 2024

ABSTRACTBackground and AimsAnti‐angiogenic therapies prolong patient survival in some malignancies but not glioblastoma. We focused on the relationship between the differentiation of glioma stem like cells (GSCs) into tumor derived endothelial cells (TDECs) and, anti‐angiogenic therapy resistance. Especially we aimed to elucidate the mechanisms of drug resistance of TDECs to anti‐angiogenic inhibitors and identify novel anti‐angiogenic drugs with clinical applications.ResultsThe mouse GSCs, 005, were differentiated into TDECs under hypoxic conditions, and TDECs had endothelial cell characteristics independent of the vascular endothelial growth factor (VEGF) pathway. In vivo, inhibition of the VEGF pathway had no anti‐tumor effect and increased the percentage of TDECs in the 005 mouse model. Novel anti‐angiogenic drugs for glioblastoma were evaluated using a tube formation assay and a drug repositioning strategy with existing blood–brain barrier permeable drugs. Drug screening revealed that the antidepressant sertraline inhibited tube formation of TDECs. Sertraline was administered to differentiated TDECs in vitro and 005 mouse models in vivo to evaluate genetic changes by RNA‐Seq and tumor regression effects by immunohistochemistry and MRI. Sertraline reduced Lama4 and Ang2 expressions of TDEC, which play an important role in non‐VEGF‐mediated angiogenesis in tumors. The combination of a VEGF receptor inhibitor axitinib, and sertraline improved survival and reduced tumor growth in the 005 mouse model.ConclusionCollectively, our findings showed the diversity of tumor vascular endothelial cells across VEGF and non‐VEGF pathways led to anti‐angiogenic resistance. The combination of axitinib and sertraline can represent an effective anti‐angiogenic therapy for glioblastoma with safe, low cost, and fast availability.
Screening Model for Bladder Cancer Early Detection With Serum miRNAs Based on Machine Learning: A Mixed‐Cohort Study Based on 16,189 Participants
Authors: Lai Cong , Hu Zhensheng , Hu Jintao , Li Zhuohang , Li Lin , Liu Mimi , Wu Zhikai , Zhou Yi , Liu Cheng , Xu Kewei 
Published: October 2024

ABSTRACTBackgroundEarly detection of bladder cancer (BCa) can have a positive impact on patients' prognosis. However, there is currently no widely accepted method for early screening of BCa. We aimed to develop an efficient, clinically applicable, and noninvasive method for the early screening of BCa by detecting specific serum miRNA levels.MethodsA mixed‐cohort (including BCa, 12 different other cancers, benign disease patients, and health population) study was conducted using a sample size of 16,189. Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. The performance of the model was evaluated using receiver operating characteristic curve and decision curve analysis on the testing dataset, and subsequently, the model with the best predictive power was selected. Furthermore, the selected model's screening performance was evaluated using both the validation set and external set.ResultsThe BCaS3miR model, utilizing only three serum miRNAs (miR‐6087, miR‐1343‐3p, and miR‐5100) and based on the KNN algorithm, is the superior screening model chosen for BCa. BCaS3miR consistently performed well in both the testing, validation, and external sets, exceeding 90% sensitivity and specificity levels. The area under the curve was 0.990 (95% CI: 0.984–0.991), 0.964 (95% CI: 0.936–0.984), and 0.917 (95% CI: 0.836–0.953) in the testing, validation, and external set. The subgroup analysis revealed that the BCaS3miR model demonstrated outstanding screening accuracy in various clinical subgroups of BCa. In addition, we developed a BCa screening scoring model (BCaSS) based on the levels of miR‐1343‐3p/miR‐6087 and miR‐5100/miR‐6087. The screening effect of BCaSS is investigated and the findings indicate that it has predictability and distinct advantages.ConclusionsUsing a mixed cohort with the largest known sample size to date, we have developed effective screening models for BCa, namely BCaS3miR and BCaSS. The models demonstrated remarkable screening accuracy, indicating potential for the early detection of BCa.
Machine Learning Model Based on Prognostic Nutritional Index for Predicting Long‐Term Outcomes in Patients With HCC Undergoing Ablation
Authors: Zhang Nan , Lin Ke , Qiao Bin , Yan Liwei , Jin Dongdong , Yang Daopeng , Yang Yue , Xie Xiaohua , Xie Xiaoyan , Zhuang Bowen 
Published: October 2024

ABSTRACTAimsTo develop multiple machine learning (ML) models based on the prognostic nutritional index (PNI) and determine the optimal model for predicting long‐term survival outcomes in hepatocellular carcinoma (HCC) patients after local ablation.MethodsFrom January 2009 to December 2019, we analyzed data from 848 primary HCC patients who underwent local ablation. ML models were constructed and evaluated using the concordance index (C‐index), concordance‐discordance area under curve (C/D AUC), and Brier scores. The optimal ML model was interpreted using the partial dependence plot (PDP) and SHapley Additive exPlanations (SHAP) framework. Additionally, the prognostic performance of our model was compared with other models.ResultsAlkaline phosphatase, preoperation alpha‐fetoprotein level, PNI, tumor number, and tumor size were identified as independent prognostic factors for ML model construction. Among the 19 ML algorithms tested, the Aorsf model showed superior performance in both the training cohort (C/D AUC: 0.733; C‐index: 0.736; Brier score: 0.133) and validation cohort (C/D AUC: 0.713; C‐index: 0.793; Brier score: 0.117). The time‐dependent AUC of the Aorsf model for predicting overall survival was as follows: 1‐, 3‐, 5‐, 7‐, and 9‐year were 0.828, 0.765, 0.781, 0.817, and 0.812 in the training cohort, 0.846, 0.859, 0.824, 0.845, and 0.874 in the validation cohort, respectively. The PDP and SHAP algorithms were employed for visual interpretation. Furthermore, time‐AUC and decision curve analysis demonstrated that the Aorsf model provided superior clinical benefits compared to other models.ConclusionThe PNI‐based Aorsf model effectively predicts long‐term survival outcomes after ablation therapy, making a significant contribution to HCC research by improving surveillance, prevention, and treatment strategies.
Four New Tirucallane Triterpenoids from the Leaves of Ailanthus Triphysa with Anti‐Inflammatory Activities
Authors: Duc Duy Nguyen , Thi Dung Duong , Thi Trang Do , Anh Bang Ngo , Hai Yen Pham , Xuan Nhiem Nguyen , Thi Cuc Nguyen , Thanh Huong Phan Thi , Viet Dung Nguyen , Huy Hoang Nguyen , Thi Hai Yen Duong , Thi Kim Thuy Nguyen , The Cuong Nguyen , Huu Tai Bui , Van Kiem Phan 
Published: October 2024

AbstractIsolation and determination of three new compounds from the leaves of Ailanthus triphysa (Dennst.) Alston with their anti‐inflammatory activity. Ten tirucallane triterpenes (1–10) including four undescribed compounds, ailantriphysas A–D (1–4), were isolated from the leaves of Ailanthus triphysa (Dennst.) Alston. Their structures were elucidated using IR, HR‐ESI‐MS, 1D‐ and 2D‐NMR spectra. Compound 1 inhibited lipopolysaccharide(LPS)‐induced nitric oxide production in RAW 264.7 cells with an IC50 value of 8.1±μM. Additionally, compound 1 also displayed significant inhibitory effects on the secretion of IL‐6 and TNF‐α at tested concentrations of 4, 8, and 16 μM.
Fertilizer Industry Innovations Supporting Climate Mitigation
Authors: Bruulsema Tom , Nigon Leanna 
Published: October 2024

AbstractFertilizers, particularly nitrogen, comprise a large part of the carbon footprint of crop production. The industry is exploring and applying innovations toward reducing emissions of greenhouse gases arising from the manufacture and use of fertilizers. Earn 1 CEU in Nutrient Management by reading this article and taking the quiz at https://web.sciencesocieties.org/Learning‐Center/Courses.
Towards environmental disclosures: The role of intellectual capital
Authors: Arora Akshita , Tiwari Ranjit 
Published: October 2024

AbstractThe aim of our study is to investigate the impact of intellectual capital (IC) and its components such as human capital, structural capital, and capital employed on the environmental disclosures (ED) of a company. The IC has been measured using value‐added intellectual coefficient (VAIC) and alternate value‐added intellectual coefficient (A_VAIC). The study employs method of moments quantile regression (MM‐QR) approach to examine the heterogeneous effects of ED within firms by extracting relevant data from ProwessIQ and Bloomberg databases. The findings of the study indicate that the relationship between ED and IC is concave implying that IC initially has a significant positive impact on ED but beyond a point, it produces negative impact. Further, it is noticed that IC's impact increases as we move from lower (25th) to higher quantile (75th), indicating that low values of IC have low impact on ED, whereas high values of IC have greater impact on ED. This is the first study to examine the impact of IC on ED. It also adds to the scarce literature on the new statistical technique of method of moments quantile regression.
Recent Advances in Electrocatalytic C−N Coupling for Urea Synthesis
Authors: Li Qiuyue , Liu Jingjing , Wu Ze , Deng Aomeng , Liu Jiani , Chen Tian , Wei Jianlong , Zhang Yiqiong , Liu Hanwen 
Published: October 2024

AbstractUrea, one of the most widely used nitrogen‐containing fertilizers globally, is essential for sustainable agriculture. Improving its production is crucial for meeting the increasing demand for fertilizers. Electrocatalytic co‐reduction of CO₂ and nitrogenous compounds (NO₂−/NO₃−) has emerged as a promising strategy for green and energy‐efficient urea synthesis. However, challenges such as slow reaction kinetics and complex multi‐step electron transfers have hindered the development of efficient urea synthesis methods. This review explores recent advances in the electrocatalytic C−N coupling process, focusing on bimetallic catalysts, metal oxide/hydroxide catalysts, and carbon‐based catalysts. The review also discusses the future prospects of designing effective catalysts for electrocatalytic C−N coupling to improve urea synthesis.