bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dirac-fermion-assisted interfacial superconductivity in epitaxial topological-insulator/iron-chalcogenide heterostructures
Authors: Yi Hemian , Hu Lun-Hui , Zhao Yi-Fan , Zhou Ling-Jie , Yan Zi-Jie , Zhang Ruoxi , Yuan Wei , Wang Zihao , Wang Ke , Hickey Danielle Reifsnyder , Richardella Anthony R. , Singleton John , Winter Laurel E. , Wu Xianxin , Chan Moses H. W. , Samarth Nitin , Liu Chao-Xing , Chang Cui-Zu 
Published: November 2023

AbstractOver the last decade, the possibility of realizing topological superconductivity (TSC) has generated much excitement. TSC can be created in electronic systems where the topological and superconducting orders coexist, motivating the continued exploration of candidate material platforms to this end. Here, we use molecular beam epitaxy (MBE) to synthesize heterostructures that host emergent interfacial superconductivity when a non-superconducting antiferromagnet (FeTe) is interfaced with a topological insulator (TI) (Bi, Sb)2Te3. By performing in-vacuo angle-resolved photoemission spectroscopy (ARPES) and ex-situ electrical transport measurements, we find that the superconducting transition temperature and the upper critical magnetic field are suppressed when the chemical potential approaches the Dirac point. We provide evidence to show that the observed interfacial superconductivity and its chemical potential dependence is the result of the competition between the Ruderman-Kittel-Kasuya-Yosida-type ferromagnetic coupling mediated by Dirac surface states and antiferromagnetic exchange couplings that generate the bicollinear antiferromagnetic order in the FeTe layer.
Probabilities of developing HIV-1 bNAb sequence features in uninfected and chronically infected individuals
Authors: Kreer Christoph , Lupo Cosimo , Ercanoglu Meryem S. , Gieselmann Lutz , Spisak Natanael , Grossbach Jan , Schlotz Maike , Schommers Philipp , Gruell Henning , Dold Leona , Beyer Andreas , Nourmohammad Armita , Mora Thierry , Walczak Aleksandra M. , Klein Florian 
Published: November 2023

AbstractHIV-1 broadly neutralizing antibodies (bNAbs) are able to suppress viremia and prevent infection. Their induction by vaccination is therefore a major goal. However, in contrast to antibodies that neutralize other pathogens, HIV-1-specific bNAbs frequently carry uncommon molecular characteristics that might prevent their induction. Here, we perform unbiased sequence analyses of B cell receptor repertoires from 57 uninfected and 46 chronically HIV-1- or HCV-infected individuals and learn probabilistic models to predict the likelihood of bNAb development. We formally show that lower probabilities for bNAbs are predictive of higher HIV-1 neutralization activity. Moreover, ranking bNAbs by their probabilities allows to identify highly potent antibodies with superior generation probabilities as preferential targets for vaccination approaches. Importantly, we find equal bNAb probabilities across infected and uninfected individuals. This implies that chronic infection is not a prerequisite for the generation of bNAbs, fostering the hope that HIV-1 vaccines can induce bNAb development in uninfected people.
Highly efficient octave-spanning long-wavelength infrared generation with a 74% quantum efficiency in a χ(2) waveguide
Authors: Hu Bo , Yang Xuemei , Wu Jiangen , Lu Siyi , Yang Hang , Long Zhe , He Linzhen , Luo Xing , Tian Kan , Wang Weizhe , Li Yang , Wu Han , Li Wenlong , Guo Chunyu , Yang Huan , Wang Qi Jie , Liang Houkun 
Published: November 2023

AbstractThe realization of compact and efficient broadband mid-infrared (MIR) lasers has enormous impacts in promoting MIR spectroscopy for various important applications. A number of well-designed waveguide platforms have been demonstrated for MIR supercontinuum and frequency comb generations based on cubic nonlinearities, but unfortunately third-order nonlinear response is inherently weak. Here, we propose and demonstrate for the first time a χ(2) micrometer waveguide platform based on birefringence phase matching for long-wavelength infrared (LWIR) laser generation with a high quantum efficiency. In a ZnGeP2-based waveguide platform, an octave-spanning spectrum covering 5–11 μm is generated through optical parametric generation (OPG). A quantum conversion efficiency of 74% as a new record in LWIR single-pass parametric processes is achieved. The threshold energy is measured as ~616 pJ, reduced by more than 1-order of magnitude as compared to those of MIR OPGs in bulk media. Our prototype micro-waveguide platform could be extended to other χ(2) birefringence crystals and trigger new frontiers of MIR integrated nonlinear photonics.
A generative adversarial network model alternative to animal studies for clinical pathology assessment
Authors: Chen Xi , Roberts Ruth , Liu Zhichao , Tong Weida 
Published: November 2023

AbstractAnimal studies are unavoidable in evaluating chemical and drug safety. Generative Adversarial Networks (GANs) can generate synthetic animal data by learning from the legacy animal study results, thus may serve as an alternative approach to assess untested chemicals. AnimalGAN, a GAN method to simulate 38 rat clinical pathology measures, was developed with significant robustness even for the drugs that vary significantly from these used during training, both in terms of chemical structure, drug class, and the year of FDA approval. AnimalGAN showed comparable results in hepatotoxicity assessment as using the real animal data and outperformed 12 conventional quantitative structure-activity relationship approaches. Using AnimalGAN, a virtual experiment of 100,000 rats ranked hepatotoxicity of three structurally similar drugs in a similar trend that has been observed in human population. AnimalGAN represented a significant step with artificial intelligence towards the global effort in replacement, reduction, and refinement (3Rs) of animal use.
LensAge index as a deep learning-based biological age for self-monitoring the risks of age-related diseases and mortality
Authors: Li Ruiyang , Chen Wenben , Li Mingyuan , Wang Ruixin , Zhao Lanqin , Lin Yuanfan , Chen Xinwei , Shang Yuanjun , Tu Xueer , Lin Duoru , Wu Xiaohang , Lin Zhenzhe , Xu Andi , Wang Xun , Wang Dongni , Zhang Xulin , Dongye Meimei , Huang Yunjian , Chen Chuan , Zhu Yi , Liu Chunqiao , Hu Youjin , Zhao Ling , Ouyang Hong , Li Miaoxin , Li Xuri , Lin Haotian 
Published: November 2023

AbstractAge is closely related to human health and disease risks. However, chronologically defined age often disagrees with biological age, primarily due to genetic and environmental variables. Identifying effective indicators for biological age in clinical practice and self-monitoring is important but currently lacking. The human lens accumulates age-related changes that are amenable to rapid and objective assessment. Here, using lens photographs from 20 to 96-year-olds, we develop LensAge to reflect lens aging via deep learning. LensAge is closely correlated with chronological age of relatively healthy individuals (R2 > 0.80, mean absolute errors of 4.25 to 4.82 years). Among the general population, we calculate the LensAge index by contrasting LensAge and chronological age to reflect the aging rate relative to peers. The LensAge index effectively reveals the risks of age-related eye and systemic disease occurrence, as well as all-cause mortality. It outperforms chronological age in reflecting age-related disease risks (p < 0.001). More importantly, our models can conveniently work based on smartphone photographs, suggesting suitability for routine self-examination of aging status. Overall, our study demonstrates that the LensAge index may serve as an ideal quantitative indicator for clinically assessing and self-monitoring biological age in humans.
A single site ruthenium catalyst for robust soot oxidation without platinum or palladium
Authors: Li Yuanfeng , Qin Tian , Wei Yuechang , Xiong Jing , Zhang Peng , Lai Kezhen , Chi Hongjie , Liu Xi , Chen Liwei , Yu Xiaolin , Zhao Zhen , Li Lina , Liu Jian 
Published: November 2023

AbstractThe quest for efficient non-Pt/Pd catalysts has proved to be a formidable challenge for auto-exhaust purification. Herein, we present an approach to construct a robust catalyst by embedding single-atom Ru sites onto the surface of CeO2 through a gas bubbling-assisted membrane deposition method. The formed single-atom Ru sites, which occupy surface lattice sites of CeO2, can improve activation efficiency for NO and O2. Remarkably, the Ru1/CeO2 catalyst exhibits exceptional catalytic performance and stability during auto-exhaust carbon particle oxidation (soot), rivaling commercial Pt-based catalysts. The turnover frequency (0.218 h−1) is a nine-fold increase relative to the Ru nanoparticle catalyst. We further show that the strong interfacial charge transfer within the atomically dispersed Ru active site greatly enhances the rate-determining step of NO oxidation, resulting in a substantial reduction of the apparent activation energy during soot oxidation. The single-atom Ru catalyst represents a step toward reducing dependence on Pt/Pd-based catalysts.
Direct time-resolved observation of surface-bound carbon dioxide radical anions on metallic nanocatalysts
Authors: Jiang Zhiwen , Clavaguéra Carine , Hu Changjiang , Denisov Sergey A. , Shen Shuning , Hu Feng , Ma Jun , Mostafavi Mehran 
Published: November 2023

AbstractTime-resolved identification of surface-bound intermediates on metallic nanocatalysts is imperative to develop an accurate understanding of the elementary steps of CO2 reduction. Direct observation on initial electron transfer to CO2 to form surface-bound CO2•− radicals is lacking due to the technical challenges. Here, we use picosecond pulse radiolysis to generate CO2•− via aqueous electron attachment and observe the stabilization processes toward well-defined nanoscale metallic sites. The time-resolved method combined with molecular simulations identifies surface-bound intermediates with characteristic transient absorption bands and distinct kinetics from nanosecond to the second timescale for three typical metallic nanocatalysts: Cu, Au, and Ni. The interfacial interactions are further investigated by varying the important factors, such as catalyst size and the presence of cation in the electrolyte. This work highlights fundamental ultrafast spectroscopy to clarify the critical initial step in the CO2 catalytic reduction mechanism.
Monolithic three-dimensional integration of RRAM-based hybrid memory architecture for one-shot learning
Authors: Li Yijun , Tang Jianshi , Gao Bin , Yao Jian , Fan Anjunyi , Yan Bonan , Yang Yuchao , Xi Yue , Li Yuankun , Li Jiaming , Sun Wen , Du Yiwei , Liu Zhengwu , Zhang Qingtian , Qiu Song , Li Qingwen , Qian He , Wu Huaqiang 
Published: November 2023

AbstractIn this work, we report the monolithic three-dimensional integration (M3D) of hybrid memory architecture based on resistive random-access memory (RRAM), named M3D-LIME. The chip featured three key functional layers: the first was Si complementary metal-oxide-semiconductor (CMOS) for control logic; the second was computing-in-memory (CIM) layer with HfAlOx-based analog RRAM array to implement neural networks for feature extractions; the third was on-chip buffer and ternary content-addressable memory (TCAM) array for template storing and matching, based on Ta2O5-based binary RRAM and carbon nanotube field-effect transistor (CNTFET). Extensive structural analysis along with array-level electrical measurements and functional demonstrations on the CIM and TCAM arrays was performed. The M3D-LIME chip was further used to implement one-shot learning, where ~96% accuracy was achieved on the Omniglot dataset while exhibiting 18.3× higher energy efficiency than graphics processing unit (GPU). This work demonstrates the tremendous potential of M3D-LIME with RRAM-based hybrid memory architecture for future data-centric applications.
Heterojunction formed via 3D-to-2D perovskite conversion for photostable wide-bandgap perovskite solar cells
Authors: Wen Jin , Zhao Yicheng , Wu Pu , Liu Yuxuan , Zheng Xuntian , Lin Renxing , Wan Sushu , Li Ke , Luo Haowen , Tian Yuxi , Li Ludong , Tan Hairen 
Published: November 2023

AbstractLight-induced halide segregation constrains the photovoltaic performance and stability of wide-bandgap perovskite solar cells and tandem cells. The implementation of an intermixed two-dimensional/three-dimensional heterostructure via solution post-treatment is a typical strategy to improve the efficiency and stability of perovskite solar cells. However, owing to the composition-dependent sensitivity of surface reconstruction, the conventional solution post-treatment is suboptimal for methylammonium-free and cesium/bromide-enriched wide-bandgap PSCs. To address this, we develop a generic three-dimensional to two-dimensional perovskite conversion approach to realize a preferential growth of wider dimensionality (n ≥ 2) atop wide-bandgap perovskite layers (1.78 eV). This technique involves depositing a well-defined MAPbI3 thin layer through a vapor-assisted two-step process, followed by its conversion into a two-dimensional structure. Such a two-dimensional/three-dimensional heterostructure enables suppressed light-induced halide segregation, reduced non-radiative interfacial recombination, and facilitated charge extraction. The wide-bandgap perovskite solar cells demonstrate a champion power conversion efficiency of 19.6% and an open-circuit voltage of 1.32 V. By integrating with the thermal-stable FAPb0.5Sn0.5I3 narrow-bandgap perovskites, our all-perovskite tandem solar cells exhibit a stabilized PCE of 28.1% and retain 90% of the initial performance after 855 hours of continuous 1-sun illumination.
Pathogenesis-adaptive polydopamine nanosystem for sequential therapy of ischemic stroke
Authors: Wu Di , Zhou Jing , Zheng Yanrong , Zheng Yuyi , Zhang Qi , Zhou Zhuchen , Chen Xiaojie , Chen Qi , Ruan Yeping , Wang Yi , Chen Zhong 
Published: November 2023

AbstractIschemic stroke is lethal cerebrovascular disease, and reperfusion as the main strategy of blood supply restoration can cause severe ischemic brain damage. Considered as the major obstacle in medication for stroke, neuroinflammation after reperfusion undergoes dynamic progression, making precision treatment for stroke a Herculean task. In this work, we report a pathogenesis-adaptive polydopamine nanosystem for sequential therapy of ischemic stroke. Intrinsic free radical scavenging and tailored mesostructure of the nanosystem can attenuate oxidative stress at the initial stage. Upon microglial overactivation at the later stage, minocycline-loaded nanosystem can timely reverse the pro-inflammatory transition in response to activated matrix metalloproteinase-2, providing on-demand regulation. Further in vivo stroke study demonstrates a higher survival rate and improved brain recovery of the sequential strategy, compared with mono-therapy and combined therapy. Complemented with satisfactory biosafety results, this adaptive nanosystem for sequential and on-demand regulation of post-stroke neuroinflammation is a promising approach to ischemic stroke therapy.
Integrated vector genomes may contribute to long-term expression in primate liver after AAV administration
Authors: Greig Jenny A. , Martins Kelly M. , Breton Camilo , Lamontagne R. Jason , Zhu Yanqing , He Zhenning , White John , Zhu Jing-Xu , Chichester Jessica A. , Zheng Qi , Zhang Zhe , Bell Peter , Wang Lili , Wilson James M. 
Published: November 2023

AbstractThe development of liver-based adeno-associated virus (AAV) gene therapies is facing concerns about limited efficiency and durability of transgene expression. We evaluated nonhuman primates following intravenous dosing of AAV8 and AAVrh10 vectors for over 2 years to better define the mechanism(s) of transduction that affect performance. High transduction of non-immunogenic transgenes was achieved, although expression declined over the first 90 days to reach a lower but stable steady state. More than 10% of hepatocytes contained single nuclear domains of vector DNA that persisted despite the loss of transgene expression. Greater reductions in vector DNA and RNA were observed with immunogenic transgenes. Genomic integration of vector sequences, including complex concatemeric structures, were detected in 1 out of 100 cells at broadly distributed loci that were not in proximity to genes associated with hepatocellular carcinoma. Our studies suggest that AAV-mediated transgene expression in primate hepatocytes occurs in two phases: high but short-lived expression from episomal genomes, followed by much lower but stable expression, likely from integrated vectors.
CRISPR–Cas9-based functional interrogation of unconventional translatome reveals human cancer dependency on cryptic non-canonical open reading frames
Authors: Zheng Caishang , Wei Yanjun , Zhang Peng , Lin Kangyu , He Dandan , Teng Hongqi , Manyam Ganiraju , Zhang Zhao , Liu Wen , Lee Hye Rin Lindsay , Tang Ximing , He Wei , Islam Nelufa , Jain Antrix , Chiu Yulun , Cao Shaolong , Diao Yarui , Meyer-Gauen Sherita , Höök Magnus , Malovannaya Anna , Li Wenbo , Hu Ming , Wang Wenyi , Xu Han , Kopetz Scott , Chen Yiwen 
Published: November 2023

AbstractEmerging evidence suggests that cryptic translation beyond the annotated translatome produces proteins with developmental or physiological functions. However, functions of cryptic non-canonical open reading frames (ORFs) in cancer remain largely unknown. To fill this gap and systematically identify colorectal cancer (CRC) dependency on non-canonical ORFs, we apply an integrative multiomic strategy, combining ribosome profiling and a CRISPR–Cas9 knockout screen with large-scale analysis of molecular and clinical data. Many such ORFs are upregulated in CRC compared to normal tissues and are associated with clinically relevant molecular subtypes. We confirm the in vivo tumor-promoting function of the microprotein SMIMP, encoded by a primate-specific, long noncoding RNA, the expression of which is associated with poor prognosis in CRC, is low in normal tissues and is specifically elevated in CRC and several other cancer types. Mechanistically, SMIMP interacts with the ATPase-forming domains of SMC1A, the core subunit of the cohesin complex, and facilitates SMC1A binding tocis-regulatory elements to promote epigenetic repression of the tumor-suppressive cell cycle regulators encoded byCDKN1AandCDKN2B. Thus, our study reveals a cryptic microprotein as an important component of cohesin-mediated gene regulation and suggests that the ‘dark’ proteome, encoded by cryptic non-canonical ORFs, may contain potential therapeutic or diagnostic targets.
The smarty4covid dataset and knowledge base as a framework for interpretable physiological audio data analysis
Authors: Zarkogianni Konstantia , Dervakos Edmund , Filandrianos George , Ganitidis Theofanis , Gkatzou Vasiliki , Sakagianni Aikaterini , Raghavendra Raghu , Max Nikias C. L. , Stamou Giorgos , Nikita Konstantina S. 
Published: November 2023

AbstractHarnessing the power of Artificial Intelligence (AI) and m-health towards detecting new bio-markers indicative of the onset and progress of respiratory abnormalities/conditions has greatly attracted the scientific and research interest especially during COVID-19 pandemic. The smarty4covid dataset contains audio signals of cough (4,676), regular breathing (4,665), deep breathing (4,695) and voice (4,291) as recorded by means of mobile devices following a crowd-sourcing approach. Other self reported information is also included (e.g. COVID-19 virus tests), thus providing a comprehensive dataset for the development of COVID-19 risk detection models. The smarty4covid dataset is released in the form of a web-ontology language (OWL) knowledge base enabling data consolidation from other relevant datasets, complex queries and reasoning. It has been utilized towards the development of models able to: (i) extract clinically informative respiratory indicators from regular breathing records, and (ii) identify cough, breath and voice segments in crowd-sourced audio recordings. A new framework utilizing the smarty4covid OWL knowledge base towards generating counterfactual explanations in opaque AI-based COVID-19 risk detection models is proposed and validated.
OIMHS: An Optical Coherence Tomography Image Dataset Based on Macular Hole Manual Segmentation
Authors: Ye Xin , He Shucheng , Zhong Xiaxing , Yu Jiafeng , Yang Shangchao , Shen Yingjiao , Chen Yiqi , Wang Yaqi , Huang Xingru , Shen Lijun 
Published: November 2023

AbstractMacular holes, one of the most common macular diseases, require timely treatment. The morphological changes on optical coherence tomography (OCT) images provided an opportunity for direct observation of the disease, and accurate segmentation was needed to identify and quantify the lesions. Developments of such algorithms had been obstructed by a lack of high-quality datasets (the OCT images and the corresponding gold standard macular hole segmentation labels), especially for supervised learning-based segmentation algorithms. In such context, we established a large OCT image macular hole segmentation (OIMHS) dataset with 3859 B-scan images of 119 patients, and each image provided four segmentation labels: retina, macular hole, intraretinal cysts, and choroid. This dataset offered an excellent opportunity for investigating the accuracy and reliability of different segmentation algorithms for macular holes and a new research insight into the further development of clinical research for macular diseases, which included the retina, lesions, and choroid in quantitative analyses.
Exponential increases in high-temperature extremes in North America
Authors: Davariashtiyani Ali , Taherkhani Mohsen , Fattahpour Seyyedfaridoddin , Vitousek Sean 
Published: November 2023

AbstractGlobal warming in the 21st century will alter the frequency of extreme climatic events, such as high-temperature anomalies and “heat waves”. Observations of extreme high temperatures during recent decades have detected upward trends in their frequency of occurrence, and recent state-of-the-art Global Climate Models (GCMs), e.g., Climate Model Intercomparison Projects (CMIPs), notably CMIP5 and CMIP6, have predicted acceleration of temperature trends and high-temperature events by 2100 under projected greenhouse-gas emission scenarios. Hence, the 21st century is expected to experience substantial shifts in the occurrence of extreme events, where present-day, extreme-but-rare high-temperature events will become common during the summer months. The increasing frequency of extreme heat may affect the health and resiliency of social, biological, and infrastructure systems in many regions worldwide, underscoring the need for accurate and reliable long-term assessments of climatic change across global and regional scales. So far, many investigations of high-temperature extremes have been carried out under end-point scenarios, e.g., by comparing GCM-projected changes in the frequency of high-temperature extremes expected in the late 21st century to the late 20th century. In this study, we use extreme value theory and decades of observations of high-temperature extremes at thousands of meteorological stations across North America to investigate continuous shifts in the frequency of extreme high-temperature events due to projected local warming trends. We find that the odds of exceedance of 50-year extreme high-temperature events increases exponentially with increases in mean local temperature. At a majority of the stations studied here, a local mean temperature increase of 0.5–1 $$^{\circ }$$

∘

C can double the odds of exceedance of 50-year extreme high-temperature events. Based on time-dependent temperature projections, the odds of exceedance of 50-year extreme high-temperature events doubles approximately every 20 years (or sooner) for $$\sim $$
∼
96% of the stations. Moreover, we find that, for $$\sim $$
∼
80% of the stations in North America, investigated here, the 50-year extreme high-temperature events will be exceeded annually before 2100.