bluuebunny/crossref_metadata_2025_split huggingface dataset:
TRIB1 regulates liver regeneration by antagonizing the NRF2-mediated antioxidant response
Authors: Sun Xinyue , Wang Shuai , Miao Xiulian , Zeng Sheng , Guo Yan , Zhou Anqi , Chen Ying , Chen Yifei , Lv Fangqiao , Fan Zhiwen , Wang Yutong , Xu Yong , Li Zilong 
Published: June 2023

AbstractRobust regenerative response post liver injuries facilitates the architectural and functional recovery of the liver. Intrahepatic redox homeostasis plays a key role in liver regeneration. In the present study, we investigated the contributory role of Tribbles homolog 1 (Trib1), a pseudokinase, in liver regeneration and the underlying mechanism. We report that Trib1 expression was transiently down-regulated in animal and cell models of liver regeneration. Further analysis revealed that hepatocyte growth factor (HGF) repressed Trib1 transcription by evicting liver X receptor (LXRα) from the Trib1 promoter. Knockdown of Trib1 enhanced whereas over-expression of Trib1 suppressed liver regeneration after partial hepatectomy in mice. Of interest, regulation of liver regenerative response by Trib1 coincided with alterations of intracellular ROS levels, GSH levels, and antioxidant genes. Transcriptional assays suggested that Trib1 influenced cellular redox status by attenuating nuclear factor erythroid 2-related factor 2 (Nrf2) activity. Mechanistically, Trib1 interacted with the C-terminus of Nrf2 thus masking a potential nuclear localization signal (NLS) and blocking nuclear accumulation of Nrf2. Finally, correlation between Trib1 expression, Nrf2 nuclear localization, and cell proliferation was identified in liver specimens taken from patients with acute liver failure. In conclusion, our data unveil a novel pathway that depicts Trib1 as a critical link between intracellular redox homeostasis and cell proliferation in liver regeneration.
Differentially private knowledge transfer for federated learning
Authors: Qi Tao , Wu Fangzhao , Wu Chuhan , He Liang , Huang Yongfeng , Xie Xing 
Published: June 2023

AbstractExtracting useful knowledge from big data is important for machine learning. When data is privacy-sensitive and cannot be directly collected, federated learning is a promising option that extracts knowledge from decentralized data by learning and exchanging model parameters, rather than raw data. However, model parameters may encode not only non-private knowledge but also private information of local data, thereby transferring knowledge via model parameters is not privacy-secure. Here, we present a knowledge transfer method named PrivateKT, which uses actively selected small public data to transfer high-quality knowledge in federated learning with privacy guarantees. We verify PrivateKT on three different datasets, and results show that PrivateKT can maximally reduce 84% of the performance gap between centralized learning and existing federated learning methods under strict differential privacy restrictions. PrivateKT provides a potential direction to effective and privacy-preserving knowledge transfer in machine intelligent systems.
Absence of localization in interacting spin chains with a discrete symmetry
Authors: Kloss Benedikt , Halimeh Jad C. , Lazarides Achilleas , Bar Lev Yevgeny 
Published: June 2023

AbstractNovel paradigms of strong ergodicity breaking have recently attracted significant attention in condensed matter physics. Understanding the exact conditions required for their emergence or breakdown not only sheds more light on thermalization and its absence in closed quantum many-body systems, but it also has potential benefits for applications in quantum information technology. A case of particular interest is many-body localization whose conditions are not yet fully settled. Here, we prove that spin chains symmetric under a combination of mirror and spin-flip symmetries and with a non-degenerate spectrum show finite spin transport at zero total magnetization and infinite temperature. We demonstrate this numerically using two prominent examples: the Stark many-body localization system (Stark-MBL) and the symmetrized many-body localization system (symmetrized–MBL). We provide evidence of delocalization at all energy densities and show that delocalization persists when the symmetry is broken. We use our results to construct two localized systems which, when coupled, delocalize each other. Our work demonstrates the dramatic effect symmetries can have on disordered systems, proves that the existence of exact resonances is not a sufficient condition for delocalization, and opens the door to generalization to higher spatial dimensions and different conservation laws.
Regulating the proximity effect of heterocycle-containing AIEgens
Authors: Zhang Jianyu , Tu Yujie , Shen Hanchen , Lam Jacky W. Y. , Sun Jianwei , Zhang Haoke , Tang Ben Zhong 
Published: June 2023

AbstractProximity effect, which refers to the low-lying (n,π*) and (π,π*) states with close energy levels, usually plays a negative role in the luminescent behaviors of heterocyclic luminogens. However, no systematic study attempts to reveal and manipulate proximity effect on luminescent properties. Here, we report a series of methylquinoxaline derivatives with different electron-donating groups, which show different photophysical properties and aggregation-induced emission behaviors. Experimental results and theoretical calculation reveal the gradually changed energy levels and different coupling effects of the closely related (n,π*) and (π,π*) states, which intrinsically regulate proximity effect and aggregation-induced emission behaviors of these luminogens. With the intrinsic nature of heterocycle-containing compounds, they are utilized for sensors and information encryption with dynamic responses to acid/base stimuli. This work reveals both positive and negative impacts of proximity effect in heterocyclic aggregation-induced emission systems and provides a perspective to develop functional and responsive luminogens with aggregation-induced emission properties.
Coherent optical control of a superconducting microwave cavity via electro-optical dynamical back-action
Authors: Qiu Liu , Sahu Rishabh , Hease William , Arnold Georg , Fink Johannes M. 
Published: June 2023

AbstractRecent quantum technologies have established precise quantum control of various microscopic systems using electromagnetic waves. Interfaces based on cryogenic cavity electro-optic systems are particularly promising, due to the direct interaction between microwave and optical fields in the quantum regime. Quantum optical control of superconducting microwave circuits has been precluded so far due to the weak electro-optical coupling as well as quasi-particles induced by the pump laser. Here we report the coherent control of a superconducting microwave cavity using laser pulses in a multimode electro-optical device at millikelvin temperature with near-unity cooperativity. Both the stationary and instantaneous responses of the microwave and optical modes comply with the coherent electro-optical interaction, and reveal only minuscule amount of excess back-action with an unanticipated time delay. Our demonstration enables wide ranges of applications beyond quantum transductions, from squeezing and quantum non-demolition measurements of microwave fields, to entanglement generation and hybrid quantum networks.
Unveiling new quantum phases in the Shastry-Sutherland compound SrCu2(BO3)2 up to the saturation magnetic field
Authors: Nomura T. , Corboz P. , Miyata A. , Zherlitsyn S. , Ishii Y. , Kohama Y. , Matsuda Y. H. , Ikeda A. , Zhong C. , Kageyama H. , Mila F. 
Published: June 2023

AbstractUnder magnetic fields, quantum magnets often undergo exotic phase transitions with various kinds of order. The discovery of a sequence of fractional magnetization plateaus in the Shastry-Sutherland compound SrCu2(BO3)2 has played a central role in the high-field research on quantum materials, but so far this system could only be probed up to half the saturation value of the magnetization. Here, we report the first experimental and theoretical investigation of this compound up to the saturation magnetic field of 140 T and beyond. Using ultrasound and magnetostriction techniques combined with extensive tensor-network calculations (iPEPS), several spin-supersolid phases are revealed between the 1/2 plateau and saturation (1/1 plateau). Quite remarkably, the sound velocity of the 1/2 plateau exhibits a drastic decrease of -50%, related to the tetragonal-to-orthorhombic instability of the checkerboard-type magnon crystal. The unveiled nature of this paradigmatic quantum system is a new milestone for exploring exotic quantum states of matter emerging in extreme conditions.
Hedgehog signaling via its ligand DHH acts as cell fate determinant during skeletal muscle regeneration
Authors: Norris Alessandra M. , Appu Ambili Bai , Johnson Connor D. , Zhou Lylybell Y. , McKellar David W. , Renault Marie-Ange , Hammers David , Cosgrove Benjamin D. , Kopinke Daniel 
Published: June 2023

AbstractSuccessful muscle regeneration relies on the interplay of multiple cell populations. However, the signals required for this coordinated intercellular crosstalk remain largely unknown. Here, we describe how the Hedgehog (Hh) signaling pathway controls the fate of fibro/adipogenic progenitors (FAPs), the cellular origin of intramuscular fat (IMAT) and fibrotic scar tissue. Using conditional mutagenesis and pharmacological Hh modulators in vivo and in vitro, we identify DHH as the key ligand that acts as a potent adipogenic brake by preventing the adipogenic differentiation of FAPs. Hh signaling also impacts muscle regeneration, albeit indirectly through induction of myogenic factors in FAPs. Our results also indicate that ectopic and sustained Hh activation forces FAPs to adopt a fibrogenic fate resulting in widespread fibrosis. In this work, we reveal crucial post-developmental functions of Hh signaling in balancing tissue regeneration and fatty fibrosis. Moreover, they provide the exciting possibility that mis-regulation of the Hh pathway with age and disease could be a major driver of pathological IMAT formation.
Nuclear myosin VI maintains replication fork stability
Authors: Shi Jie , Hauschulte Kristine , Mikicic Ivan , Maharjan Srijana , Arz Valerie , Strauch Tina , Heidelberger Jan B. , Schaefer Jonas V. , Dreier Birgit , Plückthun Andreas , Beli Petra , Ulrich Helle D. , Wollscheid Hans-Peter 
Published: June 2023

AbstractThe actin cytoskeleton is of fundamental importance for cellular structure and plasticity. However, abundance and function of filamentous actin in the nucleus are still controversial. Here we show that the actin-based molecular motor myosin VI contributes to the stabilization of stalled or reversed replication forks. In response to DNA replication stress, myosin VI associates with stalled replication intermediates and cooperates with the AAA ATPase Werner helicase interacting protein 1 (WRNIP1) in protecting these structures from DNA2-mediated nucleolytic attack. Using functionalized affinity probes to manipulate myosin VI levels in a compartment-specific manner, we provide evidence for the direct involvement of myosin VI in the nucleus and against a contribution of the abundant cytoplasmic pool during the replication stress response.
Quantum emulation of the transient dynamics in the multistate Landau-Zener model
Authors: Stehli Alexander , Brehm Jan David , Wolz Tim , Schneider Andre , Rotzinger Hannes , Weides Martin , Ustinov Alexey V. 
Published: June 2023

AbstractQuantum simulation is one of the most promising near term applications of quantum computing. Especially, systems with a large Hilbert space are hard to solve for classical computers and thus ideal targets for a simulation with quantum hardware. In this work, we study experimentally the transient dynamics in the multistate Landau-Zener model as a function of the Landau-Zener velocity. The underlying Hamiltonian is emulated by superconducting quantum circuit, where a tunable transmon qubit is coupled to a bosonic mode ensemble comprising four lumped element microwave resonators. We investigate the model for different initial states: Due to our circuit design, we are not limited to merely exciting the qubit, but can also pump the harmonic modes via a dedicated drive line. Here, the nature of the transient dynamics depends on the average photon number in the excited resonator. The greater effective coupling strength between qubit and higher Fock states results in a quasi-adiabatic transition, where coherent quantum oscillations are suppressed without the introduction of additional loss channels. Our experiments pave the way for more complex simulations with qubits coupled to an engineered bosonic mode spectrum.
Chromosome-level assemblies of cultivated water chestnut Trapa bicornis and its wild relative Trapa incisa
Authors: Qu Minghao , Fan Xiangrong , Hao Chenlu , Zheng Yi , Guo Sumin , Wang Sen , Li Wei , Xu Yanqin , Gao Lei , Chen Yuanyuan 
Published: June 2023

AbstractWater chestnut (Trapa L.) is a floating-leaved aquatic plant with high edible and medicinal value. In this study, we presented chromosome-level genome assemblies of cultivated large-seed species Trapa bicornis and its wild small-seed relative Trapa incisa by using PacBio HiFi long reads and Hi-C technology. The T. bicornis and T. incisa assemblies consisted of 479.90 Mb and 463.97 Mb contigs with N50 values of 13.52 Mb and 13.77 Mb, respectively, and repeat contents of 62.88% and 62.49%, respectively. A total of 33,306 and 33,315 protein-coding genes were predicted in T. bicornis and T. incisa assemblies, respectively. There were 159,232 structural variants affecting more than 11 thousand genes detected between the two genomes. The phylogenetic analysis indicated that the lineage leading to Trapa was diverged from the lineage to Sonneratia approximately 23 million years ago. These two assemblies provide valuable resources for future evolutionary and functional genomic research and molecular breeding of water chestnut.
Comparison of DNA extraction methods for 16S rRNA gene sequencing in the analysis of the human gut microbiome
Authors: Elie Céline , Perret Magali , Hage Hayat , Sentausa Erwin , Hesketh Amy , Louis Karen , Fritah-Lafont Asmaà , Leissner Philippe , Vachon Carole , Rostaing Hervé , Reynier Frédéric , Gervasi Gaspard , Saliou Adrien 
Published: June 2023

AbstractThe gut microbiome is widely analyzed using high-throughput sequencing, such as 16S rRNA gene amplicon sequencing and shotgun metagenomic sequencing (SMS). DNA extraction is known to have a large impact on the metagenomic analyses. The aim of this study was to compare DNA extraction protocols for 16S sequencing. In that context, four commonly used DNA extraction methods were compared for the analysis of the gut microbiota. Commercial versions were evaluated against modified protocols using a stool preprocessing device (SPD, bioMérieux) upstream DNA extraction. Stool samples from nine healthy volunteers and nine patients with a Clostridium difficile infection were extracted with all protocols and 16S sequenced. Protocols were ranked using wet- and dry-lab criteria, including quality controls of the extracted genomic DNA, alpha-diversity, accuracy using a mock community of known composition and repeatability across technical replicates. SPD improved overall efficiency of three of the four tested protocols compared with their commercial version, in terms of DNA extraction yield, sample alpha-diversity, and recovery of Gram-positive bacteria. The best overall performance was obtained for the S-DQ protocol, SPD combined with the DNeasy PowerLyser PowerSoil protocol from QIAGEN. Based on this evaluation, we strongly believe that the use of such stool preprocessing device improves both the standardization and the quality of the DNA extraction in the human gut microbiome studies.
Efficient class of estimators for finite population mean using auxiliary attribute in stratified random sampling
Authors: Singh Housila P. , Gupta Anurag , Tailor Rajesh 
Published: June 2023

AbstractThe aim of this paper is to develop more effective methods for estimating population means in sample surveys using auxiliary attributes. To achieve this goal, we introduce a modified version of the estimators proposed by Koyuncu (2013b) and Shahzad et al. (2019), as well as a new class of estimators. We derive expressions for the bias and mean squared error of these new estimators up to the first degree of approximation. Our results show that the suggested classes of estimators perform better than other existing methods, with the lowest mean squared error under optimal conditions. We also conduct an empirical investigation to support our findings.
A stacking ensemble classifier-based machine learning model for classifying pollution sources on photovoltaic panels
Authors: Khan Prince Waqas , Byun Yung Cheol , Jeong Ok-Ran 
Published: June 2023

AbstractSolar energy is a very efficient alternative for generating clean electric energy. However, pollution on the surface of solar panels reduces solar radiation, increases surface transmittance, and raises the surface temperature. All these factors cause photovoltaic (PV) panels to be less efficient. To address this problem, a stacking ensemble classifier-based machine learning model is proposed. In this study, different sources of pollution on each solar panel are used, and their power generation is recorded. The proposed model includes gradient boost, extra tree, and random forest classifiers, with the extra tree classifier serving as a meta-learner. The model takes into account various weather features during the training process, including irradiance and temperature, aiming to increase its accuracy and robustness in identifying pollution sources on the PV panel. Moreover, the proposed model is evaluated using various methods in order to examine performance metrics such as accuracy, F1 score, and precision. Results show that the model can achieve an accuracy score of 97.37%. The model’s performance is also compared to state-of-the-art machine learning models, demonstrating its superiority in accurately classifying pollution sources on PV panels. By utilizing different sources of pollution and weather features during training, the model can accurately classify different pollution sources, resulting in increased power generation efficiency and the longevity of PV panels. The main results of this study can be used to manage and maintain PV panels since the model can identify PV modules that need to be cleaned to keep producing the most power. Furthermore, the efficiency, reliability, and sustainability of PV panels can be further enhanced by the proposed model.
Automatic speaker diarization for natural conversation analysis in autism clinical trials
Authors: O’Sullivan James , Bogaarts Guy , Schoenenberger Philipp , Tillmann Julian , Slater David , Mesgarani Nima , Eule Eckhart , Kilchenmann Timothy , Murtagh Lorraine , Hipp Joerg , Lindemann Michael , Lipsmeier Florian , Cheng Wei-Yi , Nobbs David , Chatham Christopher 
Published: June 2023

AbstractChallenges in social communication is one of the core symptom domains in autism spectrum disorder (ASD). Novel therapies are under development to help individuals with these challenges, however the ability to show a benefit is dependent on a sensitive and reliable measure of treatment effect. Currently, measuring these deficits requires the use of time-consuming and subjective techniques. Objective measures extracted from natural conversations could be more ecologically relevant, and administered more frequently—perhaps giving them added sensitivity to change. While several studies have used automated analysis methods to study autistic speech, they require manual transcriptions. In order to bypass this time-consuming process, an automated speaker diarization algorithm must first be applied. In this paper, we are testing whether a speaker diarization algorithm can be applied to natural conversations between autistic individuals and their conversational partner in a natural setting at home over the course of a clinical trial. We calculated the average duration that a participant would speak for within their turn. We found a significant correlation between this feature and the Vineland Adaptive Behaviour Scales (VABS) expressive communication score (r = 0.51, p = 7 × 10–5). Our results show that natural conversations can be used to obtain measures of talkativeness, and that this measure can be derived automatically, thus showing the promise of objectively evaluating communication challenges in ASD.
Hyperphagia of female UCP1-deficient mice blunts anti-obesity effects of FGF21
Authors: Klein Hazebroek Marlou , Laterveer Rutger , Kutschke Maria , Ramšak Marčeta Vida , Barthem Clarissa S. , Keipert Susanne 
Published: June 2023

AbstractIncreasing energy expenditure through uncoupling protein 1 (UCP1) activity in thermogenic adipose tissue is widely investigated to correct diet-induced obesity (DIO). Paradoxically, UCP1-deficient male mice are resistant to DIO at room temperature. Recently, we uncovered a key role for fibroblast growth factor 21 (FGF21), a promising drug target for treatment of metabolic disease, in this phenomenon. As the metabolic action of FGF21 is so far understudied in females, we aim to investigate potential sexual dimorphisms. Here, we confirm that male UCP1 KO mice display resistance to DIO in mild cold, without significant changes in metabolic parameters. Surprisingly, females gained the same amount of body fat as WT controls. Molecular regulation was similar between UCP1 KO males and females, with an upregulation of serum FGF21, coinciding with beiging of inguinal white adipose tissue and induced lipid metabolism. While energy expenditure did not display significant differences, UCP1 KO females significantly increased their food intake. Altogether, our results indicate that hyperphagia is likely counteracting the beneficial effects of FGF21 in female mice. This underlines the importance of sex-specific studies in (pre)clinical research for personalized drug development.
Causes of death among patients with cutaneous melanoma: a US population-based study
Authors: Sadeq Mohammed Ahmed , Ashry Mohamed Hady , Ghorab Reem Mohammed Farouk , Afify Abdelrahman Yousry 
Published: June 2023

AbstractResearch on mortality outcomes and non-cancer-related causes of death in patients with cutaneous melanoma (CM) remains limited. This study aimed to identify the prevalence of non-cancer-related deaths following CM diagnosis. The data of 224,624 patients diagnosed with malignant CM in the United States between 2000 and 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We stratified our cohort based on their melanoma stage at diagnosis and further calculated standardized mortality ratios (SMRs) for each cause of death, comparing their relative risk to that of the general US population. The total number of fatalities among melanoma patients was 60,110, representing 26.8% of the total cases. The percentage of deaths is directly proportional to the disease stage, reaching 80% in distant melanoma. The highest fatalities among the localized melanoma group (25,332; 60.5%) occurred from non-cancer causes, followed by melanoma-attributable deaths (10,817; 25.8%). Conversely, melanoma is the leading cause of death in regional and distant melanoma cohorts. Cardiovascular and cerebrovascular diseases were the most prevalent non-cancer causes of death among the three disease-stage cohorts. Compared to the general population, we did not observe an increased risk of death due to non-cancer causes in the localized CM cohort, while patients diagnosed with regional and distant CMs had a statistically significant higher risk of death from all the reported major causes of death.