bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clearance of apoptotic cells by neutrophils in inflammation and cancer
Authors: Ramos Cristiano , Oehler Rudolf 
Published: January 2024

AbstractWhen a cell dies of apoptosis, it is eliminated either by neighbouring cells or by attracted professional phagocytes. Although it was generally believed that neutrophils also have the ability to perform efferocytosis, their contribution to the clearance of apoptotic cells was considered less important compared with macrophages. Therefore, this ability of neutrophils remained unexplored for a long time. Over the past decade, it has been shown that during inflammation, neutrophils contribute significantly to the clearance of apoptotic neutrophils that accumulate in large numbers at the site of tissue damage. This “neutrophil cannibalism” is accompanied by inhibition of pro-inflammatory activities of these cells, such as respiratory burst and formation of neutrophil extracellular traps (NETs). Furthermore, efferocytosing neutrophils secrete anti-inflammatory mediators and mitogens including hepatocyte growth factor (HGF), fibroblast growth factor 2 (FGF2), vascular endothelial growth factors (VEGF), and transforming growth factor beta (TGFβ). Thus, efferocytosis by neutrophils is involved in resolution of inflammation. Recent research indicates that it plays also a role in cancer. Many different solid tumours contain aggregates of dead tumour cells that have undergone spontaneous apoptosis. Their extent correlates with poor clinical outcome in most cancer types. These clusters of apoptotic tumour cells are strongly infiltrated by tumour-associated neutrophils (TANs) that acquired an anti-inflammatory and pro-resolving polarization state. This review summarizes the potential consequences discussed in the current literature. Although the picture of the role of efferocytosis by neutrophils in inflammation and cancer is becoming clearer, many questions are still unexplored.
Photonic Stochastic Emergent Storage for deep classification by scattering-intrinsic patterns
Authors: Leonetti Marco , Gosti Giorgio , Ruocco Giancarlo 
Published: January 2024

AbstractDisorder is a pervasive characteristic of natural systems, offering a wealth of non-repeating patterns. In this study, we present a novel storage method that harnesses naturally-occurring random structures to store an arbitrary pattern in a memory device. This method, the Stochastic Emergent Storage (SES), builds upon the concept of emergent archetypes, where a training set of imperfect examples (prototypes) is employed to instantiate an archetype in a Hopfield-like network through emergent processes. We demonstrate this non-Hebbian paradigm in the photonic domain by utilizing random transmission matrices, which govern light scattering in a white-paint turbid medium, as prototypes. Through the implementation of programmable hardware, we successfully realize and experimentally validate the capability to store an arbitrary archetype and perform classification at the speed of light. Leveraging the vast number of modes excited by mesoscopic diffusion, our approach enables the simultaneous storage of thousands of memories without requiring any additional fabrication efforts. Similar to a content addressable memory, all stored memories can be collectively assessed against a given pattern to identify the matching element. Furthermore, by organizing memories spatially into distinct classes, they become features within a higher-level categorical (deeper) optical classification layer.
A self-powered intracardiac pacemaker in swine model
Authors: Liu Zhuo , Hu Yiran , Qu Xuecheng , Liu Ying , Cheng Sijing , Zhang Zhengmin , Shan Yizhu , Luo Ruizeng , Weng Sixian , Li Hui , Niu Hongxia , Gu Min , Yao Yan , Shi Bojing , Wang Ningning , Hua Wei , Li Zhou , Wang Zhong Lin 
Published: January 2024

AbstractHarvesting biomechanical energy from cardiac motion is an attractive power source for implantable bioelectronic devices. Here, we report a battery-free, transcatheter, self-powered intracardiac pacemaker based on the coupled effect of triboelectrification and electrostatic induction for the treatment of arrhythmia in large animal models. We show that the capsule-shaped device (1.75 g, 1.52 cc) can be integrated with a delivery catheter for implanting in the right ventricle of a swine through the intravenous route, which effectively converts cardiac motion energy to electricity and maintains endocardial pacing function during the three-week follow-up period. We measure in vivo open circuit voltage and short circuit current of the self-powered intracardiac pacemaker of about 6.0 V and 0.2 μA, respectively. This approach exhibits up-to-date progress in self-powered medical devices and it may overcome the inherent energy shortcomings of implantable pacemakers and other bioelectronic devices for therapy and sensing.
BIDCell: Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data
Authors: Fu Xiaohang , Lin Yingxin , Lin David M. , Mechtersheimer Daniel , Wang Chuhan , Ameen Farhan , Ghazanfar Shila , Patrick Ellis , Kim Jinman , Yang Jean Y. H. 
Published: January 2024

AbstractRecent advances in subcellular imaging transcriptomics platforms have enabled high-resolution spatial mapping of gene expression, while also introducing significant analytical challenges in accurately identifying cells and assigning transcripts. Existing methods grapple with cell segmentation, frequently leading to fragmented cells or oversized cells that capture contaminated expression. To this end, we present BIDCell, a self-supervised deep learning-based framework with biologically-informed loss functions that learn relationships between spatially resolved gene expression and cell morphology. BIDCell incorporates cell-type data, including single-cell transcriptomics data from public repositories, with cell morphology information. Using a comprehensive evaluation framework consisting of metrics in five complementary categories for cell segmentation performance, we demonstrate that BIDCell outperforms other state-of-the-art methods according to many metrics across a variety of tissue types and technology platforms. Our findings underscore the potential of BIDCell to significantly enhance single-cell spatial expression analyses, enabling great potential in biological discovery.
Accurate nowcasting of cloud cover at solar photovoltaic plants using geostationary satellite images
Authors: Xia Pan , Zhang Lu , Min Min , Li Jun , Wang Yun , Yu Yu , Jia Shengjie 
Published: January 2024

AbstractAccurate nowcasting for cloud fraction is still intractable challenge for stable solar photovoltaic electricity generation. By combining continuous radiance images measured by geostationary satellite and an advanced recurrent neural network, we develop a nowcasting algorithm for predicting cloud fraction at the leading time of 0–4 h at photovoltaic plants. Based on this algorithm, a cyclically updated prediction system is also established and tested at five photovoltaic plants and several stations with cloud fraction observations in China. The results demonstrate that the cloud fraction nowcasting is efficient, high quality and adaptable. Particularly, it shows an excellent forecast performance within the first 2-hour leading time, with an average correlation coefficient close to 0.8 between the predicted clear sky ratio and actual power generation at photovoltaic plants. Our findings highlight the benefits and potential of this technique to improve the competitiveness of solar photovoltaic energy in electricity market.
Global transboundary synergies and trade-offs among Sustainable Development Goals from an integrated sustainability perspective
Authors: Xiao Huijuan , Bao Sheng , Ren Jingzheng , Xu Zhenci , Xue Song , Liu Jianguo 
Published: January 2024

AbstractDomestic attempts to advance the Sustainable Development Goals (SDGs) in a country can have synergistic and/or trade-off effects on the advancement of SDGs in other countries. Transboundary SDG interactions can be delivered through various transmission channels (e.g., trade, river flow, ocean currents, and air flow). This study quantified the transboundary interactions through these channels between 768 pairs of SDG indicators. The results showed that although high income countries only comprised 14.18% of the global population, they contributed considerably to total SDG interactions worldwide (60.60%). Transboundary synergistic effects via international trade were 14.94% more pronounced with trade partners outside their immediate geographic vicinity than with neighbouring ones. Conversely, nature-caused flows (including river flow, ocean currents, and air flow) resulted in 39.29% stronger transboundary synergistic effects among neighboring countries compared to non-neighboring ones. To facilitate the achievement of SDGs worldwide, it is essential to enhance collaboration among countries and leverage transboundary synergies.
Regio- and enantioselective synthesis of acyclic quaternary carbons via organocatalytic addition of organoborates to (Z)-Enediketones
Authors: Peng Po-Kai , Isho Andrew , May Jeremy A. 
Published: January 2024

AbstractThe chemical synthesis of molecules with closely packed atoms having their bond coordination saturated is a challenge to synthetic chemists, especially when three-dimensional control is required. The organocatalyzed asymmetric synthesis of acyclic alkenylated, alkynylated and heteroarylated quaternary carbon stereocenters via 1,4-conjugate addition is here catalyzed by 3,3´-bisperfluorotoluyl-BINOL. The highly useful products (31 examples) are produced in up to 99% yield and 97:3 er using enediketone substrates and potassium trifluoroorganoborate nucleophiles. In addition, mechanistic experiments show that the (Z)–isomer is the reactive form, ketone rotation at the site of bond formation is needed for enantioselectivity, and quaternary carbon formation is favored over tertiary. Density functional theory-based calculations show that reactivity and selectivity depend on a key n→π* donation by the unbound ketone’s oxygen lone pair to the boronate-coordinated ketone in a 5-exo-trig cyclic ouroboros transition state. Transformations of the conjugate addition products to key quaternary carbon-bearing synthetic building blocks proceed in good yield.
A ferroelectric fin diode for robust non-volatile memory
Authors: Feng Guangdi , Zhu Qiuxiang , Liu Xuefeng , Chen Luqiu , Zhao Xiaoming , Liu Jianquan , Xiong Shaobing , Shan Kexiang , Yang Zhenzhong , Bao Qinye , Yue Fangyu , Peng Hui , Huang Rong , Tang Xiaodong , Jiang Jie , Tang Wei , Guo Xiaojun , Wang Jianlu , Jiang Anquan , Dkhil Brahim , Tian Bobo , Chu Junhao , Duan Chungang 
Published: January 2024

AbstractAmong today’s nonvolatile memories, ferroelectric-based capacitors, tunnel junctions and field-effect transistors (FET) are already industrially integrated and/or intensively investigated to improve their performances. Concurrently, because of the tremendous development of artificial intelligence and big-data issues, there is an urgent need to realize high-density crossbar arrays, a prerequisite for the future of memories and emerging computing algorithms. Here, a two-terminal ferroelectric fin diode (FFD) in which a ferroelectric capacitor and a fin-like semiconductor channel are combined to share both top and bottom electrodes is designed. Such a device not only shows both digital and analog memory functionalities but is also robust and universal as it works using two very different ferroelectric materials. When compared to all current nonvolatile memories, it cumulatively demonstrates an endurance up to 1010 cycles, an ON/OFF ratio of ~102, a feature size of 30 nm, an operating energy of ~20 fJ and an operation speed of 100 ns. Beyond these superior performances, the simple two-terminal structure and their self-rectifying ratio of ~ 104 permit to consider them as new electronic building blocks for designing passive crossbar arrays which are crucial for the future in-memory computing.
CO2 hydrogenation over Fe-Co bimetallic catalysts with tunable selectivity through a graphene fencing approach
Authors: Liang Jiaming , Liu Jiangtao , Guo Lisheng , Wang Wenhang , Wang Chengwei , Gao Weizhe , Guo Xiaoyu , He Yingluo , Yang Guohui , Yasuda Shuhei , Liang Bing , Tsubaki Noritatsu 
Published: January 2024

AbstractTuning CO2 hydrogenation product distribution to obtain high-selectivity target products is of great significance. However, due to the imprecise regulation of chain propagation and hydrogenation reactions, the oriented synthesis of a single product is challenging. Herein, we report an approach to controlling multiple sites with graphene fence engineering that enables direct conversion of CO2/H2 mixtures into different types of hydrocarbons. Fe-Co active sites on the graphene fence surface present 50.1% light olefin selectivity, while the spatial Fe-Co nanoparticles separated by graphene fences achieve liquefied petroleum gas of 43.6%. With the assistance of graphene fences, iron carbides and metallic cobalt can efficiently regulate C-C coupling and olefin secondary hydrogenation reactions to achieve product-selective switching between light olefins and liquefied petroleum gas. Furthermore, it also creates a precedent for CO2 direct hydrogenation to liquefied petroleum gas via a Fischer-Tropsch pathway with the highest space-time yields compared to other reported composite catalysts.
DiffDomain enables identification of structurally reorganized topologically associating domains
Authors: Hua Dunming , Gu Ming , Zhang Xiao , Du Yanyi , Xie Hangcheng , Qi Li , Du Xiangjun , Bai Zhidong , Zhu Xiaopeng , Tian Dechao 
Published: January 2024

AbstractTopologically associating domains (TADs) are critical structural units in three-dimensional genome organization of mammalian genome. Dynamic reorganizations of TADs between health and disease states are associated with essential genome functions. However, computational methods for identifying reorganized TADs are still in the early stages of development. Here, we present DiffDomain, an algorithm leveraging high-dimensional random matrix theory to identify structurally reorganized TADs using high-throughput chromosome conformation capture (Hi–C) contact maps. Method comparison using multiple real Hi–C datasets reveals that DiffDomain outperforms alternative methods for false positive rates, true positive rates, and identifying a new subtype of reorganized TADs. Applying DiffDomain to Hi–C data from different cell types and disease states demonstrates its biological relevance. Identified reorganized TADs are associated with structural variations and epigenomic changes such as changes in CTCF binding sites. By applying to a single-cell Hi–C data from mouse neuronal development, DiffDomain can identify reorganized TADs between cell types with reasonable reproducibility using pseudo-bulk Hi–C data from as few as 100 cells per condition. Moreover, DiffDomain reveals differential cell-to-population variability and heterogeneous cell-to-cell variability in TADs. Therefore, DiffDomain is a statistically sound method for better comparative analysis of TADs using both Hi–C and single-cell Hi–C data.
Identifying the distinct roles of dual dopants in stabilizing the platinum-nickel nanowire catalyst for durable fuel cell
Authors: Gao Lei , Sun Tulai , Chen Xuli , Yang Zhilong , Li Mengfan , Lai Wenchuan , Zhang Wenhua , Yuan Quan , Huang Hongwen 
Published: January 2024

AbstractStabilizing active PtNi alloy catalyst toward oxygen reduction reaction is essential for fuel cell. Doping of specific metals is an empirical strategy, however, the atomistic insight into how dopant boosts the stability of PtNi catalyst still remains elusive. Here, with typical examples of Mo and Au dopants, we identify the distinct roles of Mo and Au in stabilizing PtNi nanowires catalysts. Specifically, due to the stronger interaction between atomic orbital for Ni-Mo and Pt-Au, the Mo dopant mainly suppresses the outward diffusion of Ni atoms while the Au dopant contributes to the stabilization of surface Pt overlayer. Inspired by this atomistic understanding, we rationally construct the PtNiMoAu nanowires by integrating the different functions of Mo and Au into one entity. Such catalyst assembled in fuel cell cathode thus presents both remarkable activity and durability, even surpassing the United States Department of Energy technical targets for 2025.
Wheat Pm55 alleles exhibit distinct interactions with an inhibitor to cause different powdery mildew resistance
Authors: Lu Chuntian , Du Jie , Chen Heyu , Gong Shuangjun , Jin Yinyu , Meng Xiangru , Zhang Ting , Fu Bisheng , Molnár István , Holušová Kateřina , Said Mahmoud , Xing Liping , Kong Lingna , Doležel Jaroslav , Li Genying , Wu Jizhong , Chen Peidu , Cao Aizhong , Zhang Ruiqi 
Published: January 2024

AbstractPowdery mildew poses a significant threat to wheat crops worldwide, emphasizing the need for durable disease control strategies. The wheat-Dasypyrum villosum T5AL·5 V#4 S and T5DL·5 V#4 S translocation lines carrying powdery mildew resistant gene Pm55 shows developmental-stage and tissue-specific resistance, whereas T5DL·5 V#5 S line carrying Pm5V confers resistance at all stages. Here, we clone Pm55 and Pm5V, and reveal that they are allelic and renamed as Pm55a and Pm55b, respectively. The two Pm55 alleles encode coiled-coil, nucleotide-binding site-leucine-rich repeat (CNL) proteins, conferring broad-spectrum resistance to powdery mildew. However, they interact differently with a linked inhibitor gene, SuPm55 to cause different resistance to wheat powdery mildew. Notably, Pm55 and SuPm55 encode unrelated CNL proteins, and the inactivation of SuPm55 significantly reduces plant fitness. Combining SuPm55/Pm55a and Pm55b in wheat does not result in allele suppression or yield penalty. Our results provide not only insights into the suppression of resistance in wheat, but also a strategy for breeding durable resistance.
Attain insensitivity to chlorine ions in magnesium alloys by impeding the diffusion process
Authors: Chen Yuyang , Fan Guodong , Xu Xinchen , Chen Yiwen , Ying Tao , Li Yangxin , Zhu Hong , Sun Wanting , Gao Yang , Yang Zongyang , Song Weiwei , Zeng Xiaoqin 
Published: January 2024

AbstractTo serve in a more aggressive chlorine (Cl−) ions-containing environment, a chlorine ions insensitivity Mg-Nd-Zr alloys is fabricated, exhibiting a stable corrosion resistance in either 3.5wt.% or 10 wt.% NaCl solution. Unlike pure Mg who exhibit a negligible protection of the matrix, a distinct “hindering effect” of Cl− diffusion caused by doping elements within the corrosion film was observed. Its underlying mechanism is demonstrated by X-ray photoelectron spectroscopy (XPS) and Density functional theory (DFT) analysis. The introducing with Nd and Zr elements can effectively passivate vacancies and alter diffusion energy of chlorine ions.
Experimental graybox quantum system identification and control
Authors: Youssry Akram , Yang Yang , Chapman Robert J. , Haylock Ben , Lenzini Francesco , Lobino Mirko , Peruzzo Alberto 
Published: January 2024

AbstractUnderstanding and controlling engineered quantum systems is key to developing practical quantum technology. However, given the current technological limitations, such as fabrication imperfections and environmental noise, this is not always possible. To address these issues, a great deal of theoretical and numerical methods for quantum system identification and control have been developed. These methods range from traditional curve fittings, which are limited by the accuracy of the model that describes the system, to machine learning (ML) methods, which provide efficient control solutions but no control beyond the output of the model, nor insights into the underlying physical process. Here we experimentally demonstrate a ‘graybox’ approach to construct a physical model of a quantum system and use it to design optimal control. We report superior performance over model fitting, while generating unitaries and Hamiltonians, which are quantities not available from the structure of standard supervised ML models. Our approach combines physics principles with high-accuracy ML and is effective with any problem where the required controlled quantities cannot be directly measured in experiments. This method naturally extends to time-dependent and open quantum systems, with applications in quantum noise spectroscopy and cancellation.
Engineered extracellular vesicle-encapsulated CHIP as novel nanotherapeutics for treatment of renal fibrosis
Authors: Ji Cheng , Zhang Jiahui , Shi Linru , Shi Hui , Xu Wenrong , Jin Jianhua , Qian Hui 
Published: January 2024

AbstractRenal interstitial fibrosis (RIF) is a fundamental pathological feature of chronic kidney disease (CKD). However, toxicity and poor renal enrichment of fibrosis inhibitors limit their further applications. In this study, a platform for CKD therapy is developed using superparamagnetic iron oxide nanoparticles (SPION) decorated mesenchymal stem cells derived extracellular vesicles with carboxyl terminus of Hsc70-interacting protein (CHIP) high expression (SPION-EVs) to achieve higher renal-targeting antifibrotic therapeutic effect. SPION-EVs selectively accumulate at the injury renal sites under an external magnetic field. Moreover, SPION-EVs deliver CHIP to induce Smad2/3 degradation in renal tubular cells which alleviates Smad2/3 activation-mediated fibrosis-like changes and collagen deposition. The extracellular vesicle engineering technology provides a potential nanoplatform for RIF therapy through CHIP-mediated Smad2/3 degradation.
The potential use of supercritical carbon dioxide in sugarcane juice processing
Authors: Pimenta Fernanda Cristina , Moraes Talita Cristiane Krice , Dacanal Gustavo Cesar , Oliveira Alessandra Lopes de , Petrus Rodrigo Rodrigues 
Published: January 2024

AbstractSugarcane juice is a nutritious and energetic drink. For its processing, the use of supercritical carbon dioxide (SC-CO2) technology as an intervention potentially capable of rendering a high quality product can be considered. This study evaluated the combined effect of SC-CO2 and mild temperatures, primarily aiming for the reduction of endogenous microorganisms and enzymes in sugarcane juice (pH~5.5). Pressures (P) ranging from 74 to 351 bar, temperatures (T) between 33 and 67 °C, and holding times (t) between 20 and 70 min were tested in a central composite rotational design. Seventeen trials were performed, comprising three replicates at the central points. Counts of aerobic mesophiles, molds and yeasts, lactic acid bacteria and coliforms at 45 °C, determination of polyphenol oxidase (PPO) and peroxidase (POD) activities, and measurement of color parameters in freshly extracted and processed juice’s samples were carried out. The pH of fresh and processed juice varied between 4.6 and 6.0, and between 4.6 and 6.3, respectively. The number of decimal reductions achieved in mesophiles, molds and yeasts, lactic acid bacteria and coliforms varied between 0.1 and 3.9, 2.1 and 4.1, 0.0 and 2.1, and 0.3 to 2.5, respectively. The percentages of PPO reduction ranged from 3.51% to 64.18%. Regarding the POD, reductions between 0.27% and 41.42% were obtained. Color variations between fresh and processed samples varied between 2.0 and 12.3. As for mesophiles, molds and yeasts reduction, and soluble solids variation, none of the variables or their interactions were significant. In terms of polyphenol oxidase (PPO) reduction, only t was significant; however, T, t, and the interaction between them significantly affected the peroxidase (POD) reduction. In regards to pH variation, P, and the interaction between T and t were significant. P, T, t, and the interaction between T and t played a significant effect on color. The combination of mild temperatures and SC-CO2 can be potentially used for cane juice preservation.