bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synergistic Effects of High‐Resolution Factors for Improving Soil Moisture Simulations Over China
Authors: Ji Peng , Yuan Xing , Jiao Yang 
Published: December 2023

AbstractUnderstanding contributions of advanced land surface models and high‐resolution model inputs (e.g., meteorological forcings and soil parameters) to root‐zone soil moisture (RSM) simulations provides critical implications for both model and data development. Previous works have investigated influences of these factors separately, without considering the interdependence between multiple factors (e.g., positive impacts of high‐resolution forcings may be reduced by coarse‐resolution parameters). To date, how to quantify this interdependence and its relative importance remain to be investigated. Here, we propose a framework to quantify independent and interdependent/synergistic effects of forcings, parameters and models on high‐resolution RSM modeling using ensemble simulations. Forty‐eight RSM simulations with different high‐resolution factors superior in both spatial resolution and data accuracy are performed over China during 2013–2017, and observations from 1,553 stations across different climate zones are used to conduct evaluation. Results show that, the increase in Kling‐Gupta efficiencies (KGEs) after combining different high‐resolution factors are larger than the sum of that using individual factors. Such synergistic effects dominate the improvement of high‐resolution modeling at national and regional scales, and contribute to consistent improvements of simulations of RSM's mean state and variability. At station scale, although independent effect increases over western China, synergistic effect contributes 42%–60% to the improved KGEs over eastern China. The positive effects of an individual high‐resolution factor on RSM modeling could be reduced by 25%–80% without synergistic effects, indicating that the synergistic developments of models, meteorological forcings and soil parameters can facilitate high‐resolution RSM modeling more efficiently than only focusing on a single factor.
The CDK12 inhibitor SR-4835 functions as a molecular glue that promotes cyclin K degradation in melanoma
Authors: Houles Thibault , Boucher Jonathan , Lavoie Geneviève , MacLeod Graham , Lin Sichun , Angers Stephane , Roux Philippe P. 
Published: December 2023

AbstractCDK12 is a transcriptional cyclin-dependent kinase (CDK) that interacts with cyclin K to regulate different aspects of gene expression. The CDK12-cyclin K complex phosphorylates several substrates, including RNA polymerase II (Pol II), and thereby regulates transcription elongation, RNA splicing, as well as cleavage and polyadenylation. Because of its implication in cancer, including breast cancer and melanoma, multiple pharmacological inhibitors of CDK12 have been identified to date, including THZ531 and SR-4835. While both CDK12 inhibitors affect Poll II phosphorylation, we found that SR-4835 uniquely promotes cyclin K degradation via the proteasome. Using loss-of-function genetic screening, we found that SR-4835 cytotoxicity depends on a functional CUL4-RBX1-DDB1 ubiquitin ligase complex. Consistent with this, we show that DDB1 is required for cyclin K degradation, and that SR-4835 promotes DDB1 interaction with the CDK12-cyclin K complex. Docking studies and structure-activity relationship analyses of SR-4835 revealed the importance of the benzimidazole side-chain in molecular glue activity. Together, our results indicate that SR-4835 acts as a molecular glue that recruits the CDK12-cyclin K complex to the CUL4-RBX1-DDB1 ubiquitin ligase complex to target cyclin K for degradation.
A novel ruthenium complex with 5-fluorouracil suppresses colorectal cancer stem cells by inhibiting Akt/mTOR signaling
Authors: Silva Valdenizia R. , Santos Luciano de S. , de Castro Maria V. L. , Dias Rosane B. , Valverde Ludmila de F. , Rocha Clarissa A. G. , Soares Milena B. P. , Quadros Claudio A. , Correa Rodrigo S. , Batista Alzir A. , Bezerra Daniel P. 
Published: December 2023

Abstract[Ru(5-FU)(PPh3)2(bipy)]PF6 (Ru/5-FU) is a novel ruthenium complex with 5-fluorouracil with promising potential against colorectal cancer (CRC). In the present study, we investigated the molecular mechanism of Ru/5-FU action in HCT116 CRC cells. Ru/5-FU exhibited potent cytotoxicity on a panel of cancer cell lines and on primary cancer cells and induced apoptosis in HCT116 CRC cells. Ru/5-FU reduced AKT1 gene transcripts, as well as the expression of Akt1 and Akt (pS473) and downstream Akt proteins mTOR (pS2448), S6 (pS235/pS236), 4EBP1 (pT36/pT45), GSK-3β (pS9) and NF-κB p65 (pS529), but not Akt upstream proteins Hsp90 and PI3K p85/p55 (pT458/pT199), indicating an inhibitory action of Akt/mTOR signaling. Ru/5-FU increased LC3B expression and reduced p62/SQSTM1 levels, indicating autophagy induction. Curiously, the autophagy inhibitors 3-methyladenine and chloroquine increased Ru/5-FU-induced cell death, indicating an induction of cytoprotective autophagy by this compound. Ru/5-FU also reduced clonogenic survival, as well as the percentage of CD133+ cells and colonosphere formation, indicating that Ru/5-FU can suppress stem cells in HCT116 cells. Ru/5-FU inhibited cell migration and invasion in wound healing assays and Transwell cell invasion assays, along with a reduction in vimentin expression and an increase in E-cadherin levels, indicating that Ru/5-FU can interfere with epithelial-mesenchymal transition. Ru/5-FU also inhibited in vivo HCT116 cell development and experimental lung metastases in mouse xenograft models. Altogether, these results indicate that Ru/5-FU is an anti-CRC chemotherapy drug candidate with the ability to suppress stemness in CRC cells by inhibiting Akt/mTOR signaling.
The involvement of E3 ubiquitin ligases in the development and progression of colorectal cancer
Authors: Chen Jie , Feng Haimei , Wang Yiting , Bai Xiaoming , Sheng Siqi , Li Huiyu , Huang Mengxi , Chu Xiaoyuan , Lei Zengjie 
Published: December 2023

AbstractTo date, colorectal cancer (CRC) still has limited therapeutic efficacy and poor prognosis and there is an urgent need for novel targets to improve the outcome of CRC patients. The highly conserved ubiquitination modification mediated by E3 ubiquitin ligases is an important mechanism to regulate the expression and function of tumor promoters or suppressors in CRC. In this review, we provide an overview of E3 ligases in modulating various biological processes in CRC, including proliferation, migration, stemness, metabolism, cell death, differentiation and immune response of CRC cells, emphasizing the pluripotency of E3 ubiquitin ligases. We further focus on the role of E3 ligases in regulating vital cellular signal pathways in CRC, such as Wnt/β-catenin pathway and NF-κB pathway. Additionally, considering the potential of E3 ligases as novel targets in the treatment of CRC, we discuss what aspects of E3 ligases can be utilized and exploited for efficient therapeutic strategies.
Soft ferroelectret ultrasound receiver for targeted peripheral neuromodulation
Authors: Li Tong , Wei Zhidong , Jin Fei , Yuan Yongjiu , Zheng Weiying , Qian Lili , Wang Hongbo , Hua Lisha , Ma Juan , Zhang Huanhuan , Gu Huaduo , Irwin Michael G. , Wang Ting , Wang Steven , Wang Zuankai , Feng Zhang-Qi 
Published: December 2023

AbstractBioelectronic medicine is a rapidly growing field where targeted electrical signals can act as an adjunct or alternative to drugs to treat neurological disorders and diseases via stimulating the peripheral nervous system on demand. However, current existing strategies are limited by external battery requirements, and the injury and inflammation caused by the mechanical mismatch between rigid electrodes and soft nerves. Here we report a wireless, leadless, and battery-free ferroelectret implant, termed NeuroRing, that wraps around the target peripheral nerve and demonstrates high mechanical conformability to dynamic motion nerve tissue. As-fabricated NeuroRing can act as an ultrasound receiver that converts ultrasound vibrations into electrostimulation pulses, thus stimulating the targeted peripheral nerve on demand. This capability is demonstrated by the precise modulation of the sacral splanchnic nerve to treat colitis, providing a framework for future bioelectronic medicines that offer an alternative to non-specific pharmacological approaches.
Chemical modulation of cytosolic BAX homodimer potentiates BAX activation and apoptosis
Authors: Gitego Nadege , Agianian Bogos , Mak Oi Wei , Kumar MV Vasantha , Cheng Emily H. , Gavathiotis Evripidis 
Published: December 2023

AbstractThe BCL-2 family protein BAX is a major regulator of physiological and pathological cell death. BAX predominantly resides in the cytosol in a quiescent state and upon stress, it undergoes conformational activation and mitochondrial translocation leading to mitochondrial outer membrane permeabilization, a critical event in apoptosis execution. Previous studies reported two inactive conformations of cytosolic BAX, a monomer and a dimer, however, it remains unclear how they regulate BAX. Here we show that, surprisingly, cancer cell lines express cytosolic inactive BAX dimers and/or monomers. Expression of inactive dimers, results in reduced BAX activation, translocation and apoptosis upon pro-apoptotic drug treatments. Using the inactive BAX dimer structure and a pharmacophore-based drug screen, we identify a small-molecule modulator, BDM19 that binds and activates cytosolic BAX dimers and prompts cells to apoptosis either alone or in combination with BCL-2/BCL-XL inhibitor Navitoclax. Our findings underscore the role of the cytosolic inactive BAX dimer in resistance to apoptosis and demonstrate a strategy to potentiate BAX-mediated apoptosis.
LinRace: cell division history reconstruction of single cells using paired lineage barcode and gene expression data
Authors: Pan Xinhai , Li Hechen , Putta Pranav , Zhang Xiuwei 
Published: December 2023

AbstractLineage tracing technology using CRISPR/Cas9 genome editing has enabled simultaneous readouts of gene expressions and lineage barcodes in single cells, which allows for inference of cell lineage and cell types at the whole organism level. While most state-of-the-art methods for lineage reconstruction utilize only the lineage barcode data, methods that incorporate gene expressions are emerging. Effectively incorporating the gene expression data requires a reasonable model of how gene expression data changes along generations of divisions. Here, we present LinRace (Lineage Reconstruction with asymmetric cell division model), which integrates lineage barcode and gene expression data using asymmetric cell division model and infers cell lineages and ancestral cell states using Neighbor-Joining and maximum-likelihood heuristics. On both simulated and real data, LinRace outputs more accurate cell division trees than existing methods. With inferred ancestral states, LinRace can also show how a progenitor cell generates a large population of cells with various functionalities.
Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles
Authors: Tan Aik Rui , Urata Shingo , Goldman Samuel , Dietschreit Johannes C. B. , Gómez-Bombarelli Rafael 
Published: December 2023

AbstractNeural networks (NNs) often assign high confidence to their predictions, even for points far out of distribution, making uncertainty quantification (UQ) a challenge. When they are employed to model interatomic potentials in materials systems, this problem leads to unphysical structures that disrupt simulations, or to biased statistics and dynamics that do not reflect the true physics. Differentiable UQ techniques can find new informative data and drive active learning loops for robust potentials. However, a variety of UQ techniques, including newly developed ones, exist for atomistic simulations and there are no clear guidelines for which are most effective or suitable for a given case. In this work, we examine multiple UQ schemes for improving the robustness of NN interatomic potentials (NNIPs) through active learning. In particular, we compare incumbent ensemble-based methods against strategies that use single, deterministic NNs: mean-variance estimation (MVE), deep evidential regression, and Gaussian mixture models (GMM). We explore three datasets ranging from in-domain interpolative learning to more extrapolative out-of-domain generalization challenges: rMD17, ammonia inversion, and bulk silica glass. Performance is measured across multiple metrics relating model error to uncertainty. Our experiments show that none of the methods consistently outperformed each other across the various metrics. Ensembling remained better at generalization and for NNIP robustness; MVE only proved effective for in-domain interpolation, while GMM was better out-of-domain; and evidential regression, despite its promise, was not the preferable alternative in any of the cases. More broadly, cost-effective, single deterministic models cannot yet consistently match or outperform ensembling for uncertainty quantification in NNIPs.
The innate interfacial elastic strain field of a transformable B2 precipitate embedded in an amorphous matrix
Authors: Fu Xiaoling , Lin Yujun , Zhu Mixun , Wang Kai , Wu Jiaqing , Tong Xing , Song Wenli , Tan Ming Jen , Yang Yuanzheng , Shen Jun , Wang Gang , Shek Chan Hung , Ritchie Robert O. 
Published: December 2023

AbstractWhen a transformable B2 precipitate is embedded in an amorphous matrix, it is often experimentally observed that the crystalline-amorphous interface not only serves as an initiation site for the martensitic transformation due to local stress concentrations, but also as an inhibitor to stabilize the transformation, the latter being attributed to the “confinement effect” exerted by the amorphous matrix, according to the Eshelby solution. These two seemingly incongruous factors are examined in this study using molecular dynamics simulations from an atomic interaction perspective. An innate strain gradient in the vicinity of the crystalline-amorphous interface is identified. The actual interface, the compressive/dilatative transition, and the interfacial maximum strain are investigated to differentiate from the conventional “interface” located within a distance of a few nanometers. Our innate interfacial elastic strain field model is applicable for the design of materials with a higher degree of martensitic transformation and controllable stress concentration, even in cryogenic environments.
Approximating outcome probabilities of linear optical circuits
Authors: Lim Youngrong , Oh Changhun 
Published: December 2023

AbstractQuasiprobability representations are important tools for analyzing a quantum system, such as a quantum state or a quantum circuit. In this work, we propose classical algorithms specialized for approximating outcome probabilities of a linear optical circuit using quasiprobability distributions. Notably, we can reduce the negativity bound of a circuit from exponential to at most polynomial for specific cases by modulating the shapes of quasiprobability distributions thanks to the symmetry of the linear optical transformation in the phase space. Consequently, our scheme provides an efficient estimation of outcome probabilities within an additive-error whose precision depends on the classicality of the input state. When the classicality is high enough, we reach a polynomial-time estimation algorithm of a probability within a multiplicative-error by an efficient sampling from a log-concave function. By choosing appropriate input states and measurements, our results provide plenty of quantum-inspired classical algorithms for approximating various matrix functions beating best-known results. Moreover, we give sufficient conditions for the classical simulability of Gaussian Boson sampling using our approximating algorithm for any (marginal) outcome probability under the poly-sparse condition.
Seeking the neural representation of statistical properties in print during implicit processing of visual words
Authors: Liu Jianyi , Fan Tengwen , Chen Yan , Zhao Jingjing 
Published: December 2023

AbstractStatistical learning (SL) plays a key role in literacy acquisition. Studies have increasingly revealed the influence of distributional statistical properties of words on visual word processing, including the effects of word frequency (lexical level) and mappings between orthography, phonology, and semantics (sub-lexical level). However, there has been scant evidence to directly confirm that the statistical properties contained in print can be directly characterized by neural activities. Using time-resolved representational similarity analysis (RSA), the present study examined neural representations of different types of statistical properties in visual word processing. From the perspective of predictive coding, an equal probability sequence with low built-in prediction precision and three oddball sequences with high built-in prediction precision were designed with consistent and three types of inconsistent (orthographically inconsistent, orthography-to-phonology inconsistent, and orthography-to-semantics inconsistent) Chinese characters as visual stimuli. In the three oddball sequences, consistent characters were set as the standard stimuli (probability of occurrence p = 0.75) and three types of inconsistent characters were set as deviant stimuli (p = 0.25), respectively. In the equal probability sequence, the same consistent and inconsistent characters were presented randomly with identical occurrence probability (p = 0.25). Significant neural representation activities of word frequency were observed in the equal probability sequence. By contrast, neural representations of sub-lexical statistics only emerged in oddball sequences where short-term predictions were shaped. These findings reveal that the statistical properties learned from long-term print environment continues to play a role in current word processing mechanisms and these mechanisms can be modulated by short-term predictions.
Gap-free 16-year (2005–2020) sub-diurnal surface meteorological observations across Florida
Authors: Peeling Julie A. , Judge Jasmeet , Misra Vasubandhu , Jayasankar C. B. , Lusher William R. 
Published: December 2023

AbstractThe sub-tropical, flat, peninsular region of Florida is subject to a unique climate with extreme weather events that impact agriculture, public health, and management of natural resources. Meteorological data at high temporal resolutions especially in tropical latitudes are essential to understand diurnal and semi-diurnal variations of climate, which are considered as the fundamental modes of climate variations of our Earth system. However, many meteorological datasets contain gaps that limit their use for validation of models and further detailed observational analysis. The objective of this paper is to apply a set of data gap filling strategies to develop a gap-free dataset with 15-minute observations for the sub-tropical region of Florida. Using data from the Florida Automated Weather Network (FAWN), methods of linear interpolation, trend continuation, reference to external sources, and nearest station substitution were applied to fill the data gaps depending on the extent of the gap. The outcome of this study provides continuous, publicly accessible surface meteorological observations for 30 FAWN stations at 15-minute intervals for years 2005–2020.
Analysis and mitigation of PQ disturbances in grid connected system using fuzzy logic based IUPQC
Authors: Ravi TatiReddy , Kumar K. Sathish , Dhanamjayulu C. , Khan Baseem , Rajalakshmi K 
Published: December 2023

AbstractRenewable energy integration introduces grid instability due to variable and intermittent sources like solar and wind, impacting reliability. This paper provides a thorough discussion of recent advancements and emerging trends in grid-integrated wind energy systems (GIWES) and grid-integrated solar energy systems (GISES). More than 70 research articles have been rigorously assessed and listed the technological and economic challenges. The increase in installations of grid-Integrating systems gives rise to challenges like as grid strain, peak shaving impacts, unpredictability of renewable energy sources (RES), and power quality disturbances. A variety of custom power devices, such as dynamic voltage restorers (DVR), static synchronous compensators (STATCOM), active power filters (APF), and unified power quality conditioners (UPQC), have gained popularity in response to these challenges. Among the various challenges, power quality disturbances, including voltage sag, swell, current and harmonics pose significant issues. To address these disturbances this work present a novel approach utilizing fuzzy logic (FL) to develop multi-feeder interline unified power-quality conditioners (MF-IUPQCs). The MF-IUPQC has three legs and three levels, each of which has four diode-clamped inverters. Switching is carried out through the use of space vector pulse width/duration modulation (SVPWM). Total harmonic distortion (THD) induced by nonlinear loads is reduced by the FLC-based MF-IUPQC, which also improves dynamic performance and offers a smooth DC-link voltage. The proposed control mechanism is implemented using MATLAB/Simulink. The fuzzy-based controller is compared to the industry-standard proportional-integral (PI) controller to determine its efficacy. Among them, the MF-IUPQC based on FLC delivers the smoothest voltage profile and the lowest THD.
Design and analysis of a flexible Ruddlesden–Popper 2D perovskite metastructure based on symmetry-protected THz-bound states in the continuum
Authors: Saadatmand Seyedeh Bita , Shokouhi Samad , Ahmadi Vahid , Hamidi Seyedeh Mehri 
Published: December 2023

AbstractA Ruddlesden–Popper 2D perovskite PEA2PbX4 (X = I, Br, and Cl) is proposed for metasurface applications. Density functional theory is used to analyze the optical, electrical, mechanical properties, moisture and thermodynamic stability of PEA2PbX4. The refractive index of PEA2PbX4 varies with the halides, resulting in 2.131, 1.901, and 1.842 for X = I, Br, and Cl, respectively. Mechanical properties with Voigt-Reuss-Hill approximations indicate that all three materials are flexible and ductile. Based on the calculations of formation energy and adsorption of water molecules, PEA2PbI4 has superior thermodynamic and moisture stability. We present a novel metasurface based on 2D-PEA2PbI4 and analyze symmetry protected-bound states in the continuum (sp-BIC) excitation. The proposed structure can excite multiple Fano quasi-BICs (q-BICs) with exceptionally high Q-factors. We verify the group theoretical analysis and explore the near-field distribution and far-field scattering of q-BICs. The findings indicate that x-polarized incident waves can excite magnetic toroidal dipole-electromagnetic-induced transparency-BIC and magnetic quadrupole-BIC, while y-polarized incident waves can excite electric toroidal dipole-BIC and electric quadrupole-BIC. The influence of meta-atom and substrate losses, array size limitations, and fabrication tolerances are also discussed. The proposed structure can be employed for applications in the THz region, such as polarization-dependent filters, bidirectional optical switches, and wearable photonic devices.