bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Eco‐Friendly Passivation Strategy of Resveratrol for Highly Efficient and Antioxidative Perovskite Solar Cells
Authors: Wu Xianhu , Bi Jieyu , Cui Guanglei , Liu Nian , Xia Gaojie , Sun Jilong , Jiang Jiaxin , Lu Ning , Li Ping , Zhao Chunyi , Zuo Zewen , Gu Min 
Published: October 2024

AbstractThe stability of perovskite solar cells is closely related to the defects in perovskite crystals, and a large number of crystal defects are caused by the solution method. In this study, resveratrol (RES), a green natural antioxidant abundant in knotweed and grape leaves, is introduced into perovskite films to passivate the defect. RES achieves defect passivation by interacting with uncoordinated Pb2+ in perovskite films. The defect formation energy of VPb and PbI on the surface of perovskite thin films is increased by RES doping, as calculated by density functional theory. The results show that the quality of the perovskite film is significantly improved, and the energy level structure of the device is optimized, and the power conversion efficiency (PCE) of the device is increased from 21.62% to 23.44%. RES can hinder the degradation of perovskite structures by O2− free radicals, and the device retained 88% of its initial PCE after over 1000 h in pure oxygen environment. The device retains 91% of the initial PCE after >1000 h at 25 °C and 50 ± 5% relative humidity. This work provides an idea for the use of natural and environmentally friendly additives to improve the efficiency and stability of devices.
GenAI for Scientific Discovery in Electrochemical Energy Storage: State‐of‐the‐Art and Perspectives from Nano‐ and Micro‐Scale
Authors: Li Shuangqi , You Fengqi 
Published: October 2024

AbstractThe transition to electric vehicles (EVs) and the increased reliance on renewable energy sources necessitate significant advancements in electrochemical energy storage systems. Fuel cells, lithium‐ion batteries, and flow batteries play a key role in enhancing the efficiency and sustainability of energy usage in transportation and storage. Despite their potential, these technologies face limitations such as high costs, material scarcity, and efficiency challenges. This research introduces a novel integration of Generative AI (GenAI) within electrochemical energy storage systems to address these issues. By leveraging advanced GenAI techniques like Generative Adversarial Networks, autoencoders, diffusion and flow‐based models, and multimodal large language models, this paper demonstrates significant improvements in material discovery, battery design, performance prediction, and lifecycle management across different types of electrochemical storage systems. The research further emphasizes the importance of nano‐ and micro‐scale interactions, providing detailed insights into optimizing these interactions for improved efficiency and longevity. Additionally, the paper discusses the challenges and future directions for integrating GenAI in energy storage research, highlighting the importance of data quality, model transparency, workflow integration, scalability, and ethical considerations. By addressing these aspects, this research sets a new benchmark for the use of GenAI in battery development, promoting sustainable, efficient, and safer energy solutions.
Enhanced Photocatalytic Degradation Performance by Micropore‐Confined Charge Transfer in Hydrogen‐Bonded Organic Framework‐Like Cocrystals
Authors: Wang Lingsong , Deng Jingheng , Bai Shuming , Wu Yunxin , Zhu Weigang 
Published: October 2024

AbstractCarrier utilization in organic photocatalytic materials is unsatisfactory due to the large exciton binding energy and short exciton diffusion length. Both donor–acceptor (D–A) strategies and porous designs are promising approaches to improve carrier utilization in photocatalysts. However, a more efficient way is to shorten the distance of exciton migration to the catalyst surface by the charge transfer (CT) process. Herein, hydrogen‐bonded organic framework‐like cocrystal (NDI‐Cor HOF‐cocrystal) is prepared with novel structures serving as a proof of concept for the approach, using N, N'‐bis (5‐isophthalate) naphthalimide (NDI‐COOH) as the porous framework and acceptor, and Coronene (Cor) as the donor unit. CT and porous engineering are integrated through cocrystal strategy. Under light irradiation, photogenerated excitons transfer and dissociate from the inner surface of the micropores on a hundred‐picosecond time scale, where efficient radical transformation and further redox reactions with adsorbed phenol molecules occur. NDI‐Cor HOF‐cocrystal photocatalytic degradation of phenol is 15 times higher than that of original HOFs, and achieves near 90% deep mineralization of phenol. Significantly, this work has designed novel HOF‐cocrystal and also provides new modification strategies for high performance organic photocatalysts.
Polar Covalent Triazine Frameworks as High‐Performance Potassium Metal Battery Cathodes
Authors: Yang Hongyan , Chen Xiaokang , Mou Yujin , Li Qi , Liu Jiaojiao , Sun Lanju , Zhai Shengliang , Deng Wei‐Qiao , Wu Hao 
Published: October 2024

AbstractThe exploration of potassium metal batteries (PMBs) has been intensified, leveraging potassium's abundant availability, low redox potential, and small Stokes radius. Covalent triazine frameworks (CTFs) stand out for their accessible nitrogen sites and customizable structures, making them attractive electrode materials. Nonetheless, there is a lack of established design principles to guide the development of high‐performance PMBs using CTFs. In this work, CTFs consisting of different monomers are used as PMB cathodes to investigate the structure‐performance correlation. The electronic structure analysis reveals the polar characteristic of a CTF derived from the tetracyanoquinodimethane monomer, setting it apart with superior capacity (161 mAh g−1 at 0.1 A g−1), rate performance (85 mAh g−1 at 5 A g−1), and stability (capacity retention of 81% after 1000 cycles) over three non‐polar counterparts in PMBs. Calculations based on density functional theory support the exceptional performance with increased K+ adsorption energy. Ultimately, among multifaceted factors, the polarity of CTF is the leading element that determines the K+ storage capability. These findings pave the way for the development of prudent CTF electrodes for high‐performance PMBs.
First Outbreak of African Swine Fever in Wild Boar in Nepal
Authors: Thakur Sameer , Rana Chandrakala , Joshi Naresh Prasad , Neupane Lokendra , Pokhrel Tirtha Raj , Shrestha Avash , Subedi Deepak 
Published: October 2024

ABSTRACTThis case report documents the first confirmed outbreak of African swine fever (ASF) in a wild boar (Sus scrofa) in Nepal. The case was identified in a wild boar carcass found in Shuklaphanta National Park in February 2023. Post‐mortem findings, including splenomegaly, haemorrhagic lymph nodes and congested organs, were suggestive of ASF, which was confirmed by real‐time PCR. Epidemiological evidence indicates potential transmission from nearby ASF‐infected domestic pigs. This case underscores the critical need for rigorous biosecurity protocols, comprehensive surveillance and targeted wildlife management strategies to prevent further transmission between domestic pig and wild boar populations.
Working Memory Is as Working Memory Does: A Pluralist Take on the Center of the Mind
Authors: Gomez‐Lavin Javier 
Published: October 2024

ABSTRACTWorking memory is thought to be the psychological capacity that enables us to maintain or manipulate information no longer in our environment for goal‐directed action. Recent work argues that working memory is not a so‐called natural kind and in turn cannot explain the cognitive processes attributed to it. This paper first clarifies the scope of this earlier critique and argues for a pluralist account of working memory. Under this account, working memory is variously realized by many mechanisms that contribute to the maintenance and manipulation of information across tasks. This view in effect updates one of the earliest pluralist formulations of working memory. Juxtaposing this view against deflationary descriptions allows us to delineate two gradients that help us chart various accounts of working memory and identify their respective theoretical commitments. In turn, we can isolate those accounts that fail to accord with the evidence supporting a pluralist view, and we can begin to rehabilitate working memory as a pluralist, and ultimately more informative, construct.
Explainable artificial intelligence for the interpretation of ensemble learning performance in algal bloom estimation
Authors: Park Jungsu , Seong Byeongchan , Park Yeonjeong , Lee Woo Hyoung , Heo Tae‐Young 
Published: October 2024

AbstractChlorophyll‐a (Chl‐a) concentrations, a key indicator of algal blooms, were estimated using the XGBoost machine learning model with 23 variables, including water quality and meteorological factors. The model performance was evaluated using three indices: root mean square error (RMSE), RMSE‐observation standard deviation ratio (RSR), and Nash–Sutcliffe efficiency. Nine datasets were created by averaging 1 hour data to cover time frequencies ranging from 1 hour to 1 month. The dataset with relatively high observation frequencies (1–24 h) maintained stability, with an RSR ranging between 0.61 and 0.65. However, the model's performance declined significantly for datasets with weekly and monthly intervals. The Shapley value (SHAP) analysis, an explainable artificial intelligence method, was further applied to provide a quantitative understanding of how environmental factors in the watershed impact the model's performance and is also utilized to enhance the practical applicability of the model in the field. The number of input variables for model construction increased sequentially from 1 to 23, starting from the variable with the highest SHAP value to that with the lowest. The model's performance plateaued after considering five or more variables, demonstrating that stable performance could be achieved using only a small number of variables, including relatively easily measured data collected by real‐time sensors, such as pH, dissolved oxygen, and turbidity. This result highlights the practicality of employing machine learning models and real‐time sensor‐based measurements for effective on‐site water quality management.Practitioner Points
XAI quantifies the effects of environmental factors on algal bloom prediction models
The effects of input variable frequency and seasonality were analyzed using XAI
XAI analysis on key variables ensures cost‐effective model development
Is there still a place for ECCO2R?
Authors: Staudinger Thomas 
Published: October 2024

AbstractThe therapeutic target of extracorporeal carbon dioxide removal (ECCO2R) is the elimination of carbon dioxide (CO2) from the blood across a gas exchange membrane without influencing oxygenation to a clinically relevant extent. In acute respiratory distress syndrome (ARDS), ECCO2R has been used to reduce tidal volume, plateau pressure, and driving pressure (“ultraprotective ventilation”). Despite achieving these goals, no benefits in outcome could be shown. Thus, in ARDS, the use of ECCO2R to achieve ultraprotective ventilation can no longer be recommended. Furthermore, ECCO2R has also been used to avoid intubation or facilitate weaning in obstructive lung failure as well as to avoid mechanical ventilation in patients during bridging to lung transplantation. Although these goals can be achieved in many patients, the effects on outcome still remain unclear due to lack of evidence. Despite involving less blood flow, smaller cannulas, and smaller gas exchange membranes compared with extracorporeal membrane oxygenation, ECCO2R bears a comparable risk of complications, especially bleeding. Trials to define indications and analyze the risk–benefit balance are needed prior to implementation of ECCO2R as a standard therapy. Consequently, until then, ECCO2R should be used in clinical studies and experienced centers only. This article is freely available.
Deutschlands erste roboterassistierte postmortale Nierentransplantation: eine gute Option bei Adipositas permagna – wenn das Team stimmt
Authors: Reimold Philipp , Groeben Christer , Keil Christian , Kormann Fabian , Peters Liliane , Volberg Christian , Kortus-Götze Birgit , Wild Johannes , Hoyer Joachim , Flegar Luka , Huber Johannes 
Published: October 2024

ZusammenfassungRoboterassistierte Nierentransplantationen werden in Europa seit 2015 durchgeführt. In Deutschland verbreitet sich die Technik langsam – zuletzt führten 3 urologische Zentren diese Art der Eingriffe durch. Im Folgenden präsentieren wir den ersten Fall einer postmortalen, roboterassistierten Nierentransplantation in Deutschland bei einem 60-jährigen Patienten. Neben der OP-Technik und dem klinischen Verlauf wird insbesondere auf Chancen dieser OP-Technik und auch deren Herausforderungen eingegangen. Zusammenfassend deckt sich die Erfahrung an unserem Zentrum mit den Erkenntnissen aus der Literatur, dass die roboterassistierte postmortale Nierentransplantation eine sichere Methode ist, um die Prinzipien der offenen Transplantationschirurgie um die Vorteile der minimal-invasiven Methodik zu ergänzen.
What is generative in generative artificial intelligence? A design-based perspective
Authors: Bordas Antoine , Le Masson Pascal , Thomas Maxime , Weil Benoit 
Published: October 2024

AbstractGenerative artificial intelligence (GenAI) models have attracted tremendous interest since the advent of ChatGPT, raising numerous opportunities and challenges. However, their generative power has not yet been studied, leaving open the question of what is truly generated by these tools. This paper addresses this question and precisely characterizes the generativity behind GenAI models. Owing to the latest advancements in engineering design, we first propose a framework for uncovering the various types of generativity. Then, we consider the main families of GenAI models and systematically analyze them to characterize their generativity within this framework. By doing so, we highlight the existence of two distinct generative levels in GenAI: one leading to the generation of new artifacts and the other leading to the generation of GenAI models themselves. We are also able to characterize the generativity of both of these levels, thus specifically confirming the generative power of GenAI and opening research avenues toward human-GenAI collaboration.
ESR Essentials: staging and restaging with FDG-PET/CT in oncology—practice recommendations by the European Society for Hybrid, Molecular and Translational Imaging
Authors: Ebner Ricarda , Sheikh Gabriel T. , Brendel Matthias , Ricke Jens , Cyran Clemens C. 
Published: October 2024

Abstract
Positron emission tomography (PET) stands as the paramount clinical molecular imaging modality, especially in oncology. Unlike conventional anatomical-morphological imaging methods such as computed tomography (CT) and magnetic resonance imaging (MRI), PET provides detailed visualizations of internal activity at the molecular and cellular levels.
18-fluorine-fluorodeoxyglucose ([18F]FDG)-PET combined with contrast-enhanced CT (ceCT) significantly improves the detection of various cancers. Appropriate patient selection is crucial, and physicians should carefully assess the appropriateness of [18F]FDG-PET/CT based on specific clinical criteria and evidence. Due to its high diagnostic accuracy, [18F]FDG-PET/CT is indispensable for evaluating the extent of disease, staging, and restaging known malignancies, and assessing the response to therapy. PET/CT imaging offers significant advantages in patient management, particularly by identifying occult metastases that might otherwise go undetected. This can help prevent unnecessary surgeries, allowing many patients to be redirected to systemic chemotherapy instead. However, it is important to note that the gold standard for surgical planning remains CT and/or MRI, depending on the body region. These imaging modalities, with or without associated angiography, provide superior contrast and spatial resolution, essential for detailed surgical preparation and planning.
[18F]FDG-PET/CT has a central role in the precise and early diagnosis of cancer, contributing significantly to personalized treatment plans. However, it has limitations, including non-tumor-specific uptake and the potential to inaccurately capture the metabolic activity of certain tumor types due to low uptake in some well-differentiated tumor cell lines. Therefore, it should be utilized in clinical scenarios where it offers crucial diagnostic insights not readily available with other imaging modalities.

Key Points

Use [18F]FDG-PET/CT selectively based on clinical appropriateness criteria and existing evidence to optimize resource utilization and minimize patient exposure.

Employ [18F]FDG-PET/CT in treatment planning and monitoring, particularly for assessing chemotherapy or radiotherapy response in FDG-avid lymphoma and solid tumors.

When available, [18F]FDG-PET/CT can be integrated with other diagnostic tools, such as MRI, to enhance overall diagnostic accuracy.
Epigenetic landscape reorganisation and reactivation of embryonic development genes are associated with malignancy in IDH-mutant astrocytoma
Authors: Ghisai Santoesha A. , van Hijfte Levi , Vallentgoed Wies R. , Tesileanu C. Mircea S. , de Heer Iris , Kros Johan M. , Sanson Marc , Gorlia Thierry , Wick Wolfgang , Vogelbaum Michael A. , Brandes Alba A. , Franceschi Enrico , Clement Paul M. , Nowak Anna K. , Golfinopoulos Vassilis , van den Bent Martin J. , French Pim J. , Hoogstrate Youri 
Published: October 2024

AbstractAccurate grading of IDH-mutant gliomas defines patient prognosis and guides the treatment path. Histological grading is challenging, and aside from CDKN2A/B homozygous deletions in IDH-mutant astrocytomas, there are no other objective molecular markers used for grading. RNA-sequencing was conducted on primary IDH-mutant astrocytomas (n = 138) included in the prospective CATNON trial, which was performed to assess the prognostic effect of adjuvant and concurrent temozolomide. We integrated the RNA-sequencing data with matched DNA-methylation and NGS data. We also used multi-omics data from IDH-mutant astrocytomas included in the TCGA dataset and validated results on matched primary and recurrent samples from the GLASS-NL study. Since discrete classes do not adequately capture grading of these tumours, we utilised DNA-methylation profiles to generate a Continuous Grading Coefficient (CGC) based on classification scores from a CNS-tumour classifier. CGC was an independent predictor of survival outperforming current WHO-CNS5 and methylation-based classification. Our RNA-sequencing analysis revealed four distinct transcription clusters that were associated with (i) upregulation of cell cycling genes; (ii) downregulation of glial differentiation genes; (iii) upregulation of embryonic development genes (e.g. HOX, PAX, and TBX) and (iv) upregulation of extracellular matrix genes. The upregulation of embryonic development genes was associated with a specific increase of CpG island methylation near these genes. Higher grade IDH-mutant astrocytomas have DNA-methylation signatures that, on the RNA level, are associated with increased cell cycling, tumour cell de-differentiation and extracellular matrix remodelling. These combined molecular signatures can serve as an objective marker for grading of IDH-mutant astrocytomas.
ACE2 and TMPRSS2 in human kidney tissue and urine extracellular vesicles with age, sex, and COVID-19
Authors: Bach Marie Lykke , Laftih Sara , Andresen Jesper K. , Pedersen Rune M. , Andersen Thomas Emil , Madsen Lone W. , Madsen Kirsten , Hinrichs Gitte R. , Zachar Rikke , Svenningsen Per , Lund Lars , Johansen Isik S. , Hansen Lennart Friis , Palarasah Yaseelan , Jensen Boye L. 
Published: October 2024

AbstractSARS-CoV-2 virus infects cells by engaging with ACE2 requiring protease TMPRSS2. ACE2 is highly expressed in kidneys. Predictors for severe disease are high age and male sex. We hypothesized that ACE2 and TMPRSS2 proteins are more abundant (1) in males and with increasing age in kidney and (2) in urine and extracellular vesicles (EVs) from male patients with COVID-19 and (3) SARS-CoV-2 is present in urine and EVs during infection. Kidney cortex samples from patients subjected to cancer nephrectomy (male/female; < 50 years/˃75 years, n = 24; ˃80 years, n = 15) were analyzed for ACE2 and TMPRSS2 protein levels. Urine from patients hospitalized with SARS-CoV-2 infection was analyzed for ACE2 and TMPRSS2. uEVs were used for immunoblotting and SARS-CoV-2 mRNA and antigen detection. Tissue ACE2 and TMPRSS2 protein levels did not change with age. ACE2 was not more abundant in male kidneys in any age group. ACE2 protein was associated with proximal tubule apical membranes in cortex. TMPRSS2 was observed predominantly in the medulla. ACE2 was elevated significantly in uEVs and urine from patients with COVID-19 with no sex difference compared with urine from controls w/wo albuminuria. TMPRSS2 was elevated in uEVs from males compared to female. ACE2 and TMPRSS2 did not co-localize in uEVs/apical membranes. SARS-CoV-2 nucleoprotein and mRNA were not detected in urine. Higher kidney ACE2 protein abundance is unlikely to explain higher susceptibility to SARS-CoV-2 infection in males. Kidney tubular cells appear not highly susceptible to SARS-CoV-2 infection. Loss of ACE2 into urine in COVID could impact susceptibility and angiotensin metabolism.
Characterization of human placental fetal vessels in gestational diabetes mellitus
Authors: Carstens Philine S. , Brendel Heike , Villar-Ballesteros M. Leyre , Mittag Jennifer , Hengst Clara , Brunssen Coy , Birdir Cahit , Taylor Paul D. , Poston Lucilla , Morawietz Henning 
Published: October 2024

AbstractGestational diabetes mellitus is one of the most common complications during pregnancy. Its prevalence is rapidly increasing worldwide. Gestational diabetes mellitus is leading to an elevated risk for the development of endothelial dysfunction and cardiovascular diseases both in the mother and the child in later life. The underlying pathophysiological mechanisms are not well-understood. Therefore, we aimed to characterize the endothelial function in fetal placental vessels from mothers with gestational diabetes mellitus. In this study, we distinguished between insulin-treated and diet-controlled gestational diabetes mothers and compared them to a normoglycemic control group. The clinical data confirmed pre-conceptional overweight as a risk factor in women with insulin-treated gestational diabetes mellitus. The insulin-treated gestational diabetes group was also characterized by a recent family history of diabetes compared to mothers of the control or diet-controlled gestational diabetes group. Analyses of blood serum from umbilical cords suggested a reduced fetal insulin metabolism in the insulin-treated gestational diabetes group. Vascular function analysis in fetal placental vessels revealed an altered substance P-induced vasorelaxation in vessels from patients with insulin-dependent gestational diabetes. Inhibition of nitric oxide synthase affected only fetal vessel segments from the control group or diet-controlled gestational diabetes group, but not from insulin-dependent gestational diabetes. Finally, we found a significantly decreased substance P receptor (TACR1) mRNA expression in fetal vessel segments from patients with insulin-treated gestational diabetes. In conclusion, we provide evidence that different pathophysiological mechanisms might be responsible for the development of insulin-treated versus diet-controlled gestational diabetes. Only in fetal vessels from patients with insulin-treated gestational diabetes were we able to detect an endothelial dysfunction and a reduced fetal insulin conversion. This provides novel insights into the pathophysiology of the subtypes of gestational diabetes.