bluuebunny/crossref_metadata_2025_split huggingface dataset:
GRDL: A New Global Reservoir Area‐Storage‐Depth Data Set Derived Through Deep Learning‐Based Bathymetry Reconstruction
Authors: Hao Zhen , Chen Fang , Jia Xiaofeng , Cai Xiaobin , Yang Chao , Du Yun , Ling Feng 
Published: January 2024

AbstractReservoirs play a critical role in the global water cycle by regulating the flow of water from the environment into human systems. Accurate estimation of the area‐storage‐depth relationships for global reservoirs is essential for effective hydrological modeling and reservoir storage monitoring. Bathymetry reconstruction presents a promising approach to derive this information. Current bathymetry methods either rely on simple approximations or are constrained by dependence on altimetry data or field survey data. To overcome these limitations, this study presents a pioneering approach involving training a deep learning model to reconstruct bathymetry and establish precise area‐storage‐depth relationships. We trained the deep learning model with approximately 160,000 simulated reservoirs derived from Shuttle Radar Topography Mission (SRTM) and fine‐tuned the model based on hundreds of reservoirs with bathymetry data. By employing the trained model and SRTM, the bathymetry of 7,250 reservoirs in the Global Reservoir and Dam Database were subsequently reconstructed. The method is validated against comprehensive reference data sets, including 54 test reservoirs with bathymetry data, 118 satellite altimetry‐based reservoirs, and 68 LiDAR‐based reservoirs. The reconstructed bathymetry achieves a mean absolute error of 7.87 m and a mean error of +2.05 m for the test reservoirs. The validation against satellite altimetry and LiDAR‐based references significantly outperforms previous geometric approximation techniques, with median normalized root mean square error (NRMSE) values of 20.6% for area‐storage and 22.1% for area‐level curves. Additionally, the reservoir storage variations are estimated with precision, outperforming previous methods. The proposed deep learning‐based approach presents a robust solution for accurate reservoir bathymetry estimation and establishes more reliable area‐storage‐depth relationships for reservoirs worldwide.
Hedgehog signalling is involved in acquired resistance to KRASG12C inhibitors in lung cancer cells
Authors: Lee Chaeyoung , Yi Jawoon , Park Jihwan , Ahn Byungyong , Won Young-Wook , Jeon JiHeung , Lee Byung Ju , Cho Wha Ja , Park Jeong Woo 
Published: January 2024

AbstractAlthough KRASG12C inhibitors have shown promising activity in lung adenocarcinomas harbouring KRASG12C, acquired resistance to these therapies eventually occurs in most patients. Re-expression of KRAS is thought to be one of the main causes of acquired resistance. However, the mechanism through which cancer cells re-express KRAS is not fully understood. Here, we report that the Hedgehog signal is induced by KRASG12C inhibitors and mediates KRAS re-expression in cancer cells treated with a KRASG12C inhibitor. Further, KRASG12C inhibitors induced the formation of primary cilia and activated the Hedgehog-GLI-1 pathway. GLI-1 binds to the KRAS promoter region, enhancing KRAS promoter activity and KRAS expression. Inhibition of GLI using siRNA or the smoothened (Smo) inhibitor suppressed re-expression of KRAS in cells treated with a KRASG12C inhibitor. In addition, we demonstrate that KRASG12C inhibitors decreased Aurora kinase A (AURKA) levels in cancer cells, and inhibition of AURKA using siRNA or inhibitors led to increased expression levels of GLI-1 and KRAS even in the absence of KRAS inhibitor. Ectopic expression of AURKA attenuated the effect of KRASG12C inhibitors on the expression of GLI-1 and re-expression of KRAS. Together, these findings demonstrate the important role of AURKA, primary cilia, and Hedgehog signals in the re-expression of KRAS and therefore the induction of acquired resistance to KRASG12C inhibitors, and provide a rationale for targeting Hedgehog signalling to overcome acquired resistance to KRASG12C inhibitors.
Targeting POLRMT by a first-in-class inhibitor IMT1 inhibits osteosarcoma cell growth in vitro and in vivo
Authors: Kong Yang , Li Xiangrong , Zhang Huanle , Fu Bin , Jiang Hua-Ye , Yang Hui-Lin , Dai Jin 
Published: January 2024

AbstractOsteosarcoma (OS) is a highly aggressive form of bone cancer that predominantly affects adolescents and young adults. In this study, we have undertaken an investigation into the potential anti-OS cell activity of IMT1 (inhibitor of mitochondrial transcription 1), a first-in-class inhibitor of RNA polymerase mitochondrial (POLRMT). IMT1 exhibited a profound inhibitory effect on cell survival, proliferation, cell cycle progression, and migration in primary and immortalized OS cells. Furthermore, this POLRMT inhibitor elicited apoptosis in the OS cells, without, however, inducing cytotoxicity in human osteoblasts or osteoblastic cells. IMT1 disrupted mitochondrial functions in OS cells, resulting in mitochondrial depolarization, oxidative injury, lipid peroxidation, and ATP reduction in OS cells. Silencing POLRMT using targeted shRNA closely mimicked the actions of IMT1 and exerted potent anti-OS cell activity. Importantly, IMT1’s effectiveness was diminished in POLRMT-silenced OS cells. Subsequent investigations revealed that IMT1 suppressed the activation of the Akt-mammalian target of rapamycin (mTOR) cascade in OS cells. IMT1 treatment or POLRMT silencing in primary OS cells led to a significant reduction in Akt1-S6K-S6 phosphorylation. Conversely, it was enhanced upon POLRMT overexpression. The restoration of Akt-mTOR activation through the introduction of a constitutively active S473D mutant Akt1 (caAkt1) mitigated IMT1-induced cytotoxicity in OS cells. In vivo, oral administration of IMT1 robustly curtailed the growth of OS xenografts in nude mice. Furthermore, IMT1 suppressed POLRMT activity, impaired mitochondrial function, repressed Akt-mTOR activation, and induced apoptosis within xenograft tissues. Collectively, these findings underscore the potent growth-inhibitory effects attributed to IMT1 via targeted POLRMT inhibition. The utilization of this POLRMT inhibitor carries substantial therapeutic promise in the context of OS treatment.
Antibody-dependent enhancement of toxicity of myotoxin II from Bothrops asper
Authors: Sørensen Christoffer V. , Fernández Julián , Adams Anna Christina , Wildenauer Helen H. K. , Schoffelen Sanne , Ledsgaard Line , Pucca Manuela B. , Fiebig Michael , Cerni Felipe A. , Tulika Tulika , Voldborg Bjørn G. , Karatt-Vellatt Aneesh , Morth J. Preben , Ljungars Anne , Grav Lise M. , Lomonte Bruno , Laustsen Andreas H. 
Published: January 2024

AbstractImproved therapies are needed against snakebite envenoming, which kills and permanently disables thousands of people each year. Recently developed neutralizing monoclonal antibodies against several snake toxins have shown promise in preclinical rodent models. Here, we use phage display technology to discover a human monoclonal antibody and show that this antibody causes antibody-dependent enhancement of toxicity (ADET) of myotoxin II from the venomous pit viper, Bothrops asper, in a mouse model of envenoming that mimics a snakebite. While clinical ADET related to snake venom has not yet been reported in humans, this report of ADET of a toxin from the animal kingdom highlights the necessity of assessing even well-known antibody formats in representative preclinical models to evaluate their therapeutic utility against toxins or venoms. This is essential to avoid potential deleterious effects as exemplified in the present study.
Microscopic mechanisms of pressure-induced amorphous-amorphous transitions and crystallisation in silicon
Authors: Fan Zhao , Tanaka Hajime 
Published: January 2024

AbstractSome low-coordination materials, including water, silica, and silicon, exhibit polyamorphism, having multiple amorphous forms. However, the microscopic mechanism and kinetic pathway of amorphous-amorphous transition (AAT) remain largely unknown. Here, we use a state-of-the-art machine-learning potential and local structural analysis to investigate the microscopic kinetics of AAT in silicon after a rapid pressure change. We find that the transition from low-density-amorphous (LDA) to high-density-amorphous (HDA) occurs through nucleation and growth, resulting in non-spherical interfaces that underscore the mechanical nature of AAT. In contrast, the reverse transition occurs through spinodal decomposition. Further pressurisation transforms LDA into very-high-density amorphous (VHDA), with HDA serving as an intermediate state. Notably, the final amorphous states are inherently unstable, transitioning into crystals. Our findings demonstrate that AAT and crystallisation are driven by joint thermodynamic and mechanical instabilities, assisted by preordering, occurring without diffusion. This unique mechanical and diffusion-less nature distinguishes AAT from liquid-liquid transitions.
A Machine Learning-Driven Virtual Biopsy System For Kidney Transplant Patients
Authors: Yoo Daniel , Divard Gillian , Raynaud Marc , Cohen Aaron , Mone Tom D. , Rosenthal John Thomas , Bentall Andrew J. , Stegall Mark D. , Naesens Maarten , Zhang Huanxi , Wang Changxi , Gueguen Juliette , Kamar Nassim , Bouquegneau Antoine , Batal Ibrahim , Coley Shana M. , Gill John S. , Oppenheimer Federico , De Sousa-Amorim Erika , Kuypers Dirk R. J. , Durrbach Antoine , Seron Daniel , Rabant Marion , Van Huyen Jean-Paul Duong , Campbell Patricia , Shojai Soroush , Mengel Michael , Bestard Oriol , Basic-Jukic Nikolina , Jurić Ivana , Boor Peter , Cornell Lynn D. , Alexander Mariam P. , Toby Coates P. , Legendre Christophe , Reese Peter P. , Lefaucheur Carmen , Aubert Olivier , Loupy Alexandre 
Published: January 2024

AbstractIn kidney transplantation, day-zero biopsies are used to assess organ quality and discriminate between donor-inherited lesions and those acquired post-transplantation. However, many centers do not perform such biopsies since they are invasive, costly and may delay the transplant procedure. We aim to generate a non-invasive virtual biopsy system using routinely collected donor parameters. Using 14,032 day-zero kidney biopsies from 17 international centers, we develop a virtual biopsy system. 11 basic donor parameters are used to predict four Banff kidney lesions: arteriosclerosis, arteriolar hyalinosis, interstitial fibrosis and tubular atrophy, and the percentage of renal sclerotic glomeruli. Six machine learning models are aggregated into an ensemble model. The virtual biopsy system shows good performance in the internal and external validation sets. We confirm the generalizability of the system in various scenarios. This system could assist physicians in assessing organ quality, optimizing allograft allocation together with discriminating between donor derived and acquired lesions post-transplantation.
Towards estimating the number of strains that make up a natural bacterial population
Authors: Viver Tomeu , Conrad Roth E. , Rodriguez-R Luis M. , Ramírez Ana S. , Venter Stephanus N. , Rocha-Cárdenas Jairo , Llabrés Mercè , Amann Rudolf , Konstantinidis Konstantinos T. , Rossello-Mora Ramon 
Published: January 2024

AbstractWhat a strain is and how many strains make up a natural bacterial population remain elusive concepts despite their apparent importance for assessing the role of intra-population diversity in disease emergence or response to environmental perturbations. To advance these concepts, we sequenced 138 randomly selected Salinibacter ruber isolates from two solar salterns and assessed these genomes against companion short-read metagenomes from the same samples. The distribution of genome-aggregate average nucleotide identity (ANI) values among these isolates revealed a bimodal distribution, with four-fold lower occurrence of values between 99.2% and 99.8% relative to ANI >99.8% or <99.2%, revealing a natural “gap” in the sequence space within species. Accordingly, we used this ANI gap to define genomovars and a higher ANI value of >99.99% and shared gene-content >99.0% to define strains. Using these thresholds and extrapolating from how many metagenomic reads each genomovar uniquely recruited, we estimated that –although our 138 isolates represented about 80% of the Sal. ruber population– the total population in one saltern pond is composed of 5,500 to 11,000 genomovars, the great majority of which appear to be rare in-situ. These data also revealed that the most frequently recovered isolate in lab media was often not the most abundant genomovar in-situ, suggesting that cultivation biases are significant, even in cases that cultivation procedures are thought to be robust. The methodology and ANI thresholds outlined here should represent a useful guide for future microdiversity surveys of additional microbial species.
Selective CK1α degraders exert antiproliferative activity against a broad range of human cancer cell lines
Authors: Nishiguchi Gisele , Mascibroda Lauren G. , Young Sarah M. , Caine Elizabeth A. , Abdelhamed Sherif , Kooijman Jeffrey J. , Miller Darcie J. , Das Sourav , McGowan Kevin , Mayasundari Anand , Shi Zhe , Barajas Juan M. , Hiltenbrand Ryan , Aggarwal Anup , Chang Yunchao , Mishra Vibhor , Narina Shilpa , Thomas Melvin , Loughran Allister J. , Kalathur Ravi , Yu Kaiwen , Zhou Suiping , Wang Xusheng , High Anthony A. , Peng Junmin , Pruett-Miller Shondra M. , Daniels Danette L. , Urh Marjeta , Shelat Anang A. , Mullighan Charles G. , Riching Kristin M. , Zaman Guido J. R. , Fischer Marcus , Klco Jeffery M. , Rankovic Zoran 
Published: January 2024

AbstractMolecular-glue degraders are small molecules that induce a specific interaction between an E3 ligase and a target protein, resulting in the target proteolysis. The discovery of molecular glue degraders currently relies mostly on screening approaches. Here, we describe screening of a library of cereblon (CRBN) ligands against a panel of patient-derived cancer cell lines, leading to the discovery of SJ7095, a potent degrader of CK1α, IKZF1 and IKZF3 proteins. Through a structure-informed exploration of structure activity relationship (SAR) around this small molecule we develop SJ3149, a selective and potent degrader of CK1α protein in vitro and in vivo. The structure of SJ3149 co-crystalized in complex with CK1α + CRBN + DDB1 provides a rationale for the improved degradation properties of this compound. In a panel of 115 cancer cell lines SJ3149 displays a broad antiproliferative activity profile, which shows statistically significant correlation with MDM2 inhibitor Nutlin-3a. These findings suggest potential utility of selective CK1α degraders for treatment of hematological cancers and solid tumors.
Enhancing aortic valve drug delivery with PAR2-targeting magnetic nano-cargoes for calcification alleviation
Authors: Chen Jinyong , Ren Tanchen , Xie Lan , Hu Haochang , Li Xu , Maitusong Miribani , Zhou Xuhao , Hu Wangxing , Xu Dilin , Qian Yi , Cheng Si , Yu Kaixiang , Wang Jian`an , Liu Xianbao 
Published: January 2024

AbstractCalcific aortic valve disease is a prevalent cardiovascular disease with no available drugs capable of effectively preventing its progression. Hence, an efficient drug delivery system could serve as a valuable tool in drug screening and potentially enhance therapeutic efficacy. However, due to the rapid blood flow rate associated with aortic valve stenosis and the lack of specific markers, achieving targeted drug delivery for calcific aortic valve disease has proved to be challenging. Here we find that protease-activated-receptor 2 (PAR2) expression is up-regulated on the plasma membrane of osteogenically differentiated valvular interstitial cells. Accordingly, we develop a magnetic nanocarrier functionalized with PAR2-targeting hexapeptide for dual-active targeting drug delivery. We show that the nanocarriers effectively deliver XCT790—an anti-calcification drug—to the calcified aortic valve under extra magnetic field navigation. We demonstrate that the nano-cargoes consequently inhibit the osteogenic differentiation of valvular interstitial cells, and alleviate aortic valve calcification and stenosis in a high-fat diet-fed low-density lipoprotein receptor-deficient (Ldlr−/−) mouse model. This work combining PAR2- and magnetic-targeting presents an effective targeted drug delivery system for treating calcific aortic valve disease in a murine model, promising future clinical translation.
Acceleration of the ocean warming from 1961 to 2022 unveiled by large-ensemble reanalyses
Authors: Storto Andrea , Yang Chunxue 
Published: January 2024

AbstractLong-term changes in ocean heat content (OHC) represent a fundamental global warming indicator and are mostly caused by anthropogenic climate-altering gas emissions. OHC increases heavily threaten the marine environment, therefore, reconstructing OHC before the well-instrumented period (i.e., before the Argo floats deployment in the mid-2000s) is crucial to understanding the multi-decadal climate change in the ocean. Here, we shed light on ocean warming and its uncertainty for the 1961-2022 period through a large ensemble reanalysis system that spans the major sources of uncertainties. Results indicate a 62-year warming of 0.43 ± 0.08 W m−2, and a statistically significant acceleration rate equal to 0.15 ± 0.04 W m−2 dec−1, locally peaking at high latitudes. The 11.6% of the global ocean area reaches the maximum yearly OHC in 2022, almost doubling any previous year. At the regional scale, major OHC uncertainty is found in the Tropics; at the global scale, the uncertainty represents about 40% and 15% of the OHC variability, respectively before and after the mid-2000s. The uncertainty of regional trends is mostly affected by observation calibration (especially at high latitudes), and sea surface temperature data uncertainty (especially at low latitudes).
An artificial intelligence-based model for optimal conjunctive operation of surface and groundwater resources
Authors: Akbarifard Saeid , Madadi Mohamad Reza , Zounemat-Kermani Mohammad 
Published: January 2024

AbstractA hybrid simulation-optimization model is proposed for the optimal conjunctive operation of surface and groundwater resources. This second-level model is created by finding and combining the best aspects of two resilient metaheuristics, the moth swarm algorithm and the symbiotic organization search algorithm, and then connecting the resulting algorithm to an artificial neural network simulator. For assessment of the developed model efficiency, its results are compared with two first-level simulation-optimization models. The comparisons reveal that the operation policies obtained by the developed second-level model can reliably supply more than 99% of the total demands in the study regions, indicating its superior efficiency compared to the two other first-level models. In addition, the highest sustainability index in the study regions belongs to the proposed model. Comparing the results of this research with those of other recent studies confirm the supremacy of the developed second-level model over several previously developed models.
Spin-resolved topology and partial axion angles in three-dimensional insulators
Authors: Lin Kuan-Sen , Palumbo Giandomenico , Guo Zhaopeng , Hwang Yoonseok , Blackburn Jeremy , Shoemaker Daniel P. , Mahmood Fahad , Wang Zhijun , Fiete Gregory A. , Wieder Benjamin J. , Bradlyn Barry 
Published: January 2024

AbstractSymmetry-protected topological crystalline insulators (TCIs) have primarily been characterized by their gapless boundary states. However, in time-reversal- ($${{{{{{{\mathcal{T}}}}}}}}$$
T
-) invariant (helical) 3D TCIs—termed higher-order TCIs (HOTIs)—the boundary signatures can manifest as a sample-dependent network of 1D hinge states. We here introduce nested spin-resolved Wilson loops and layer constructions as tools to characterize the intrinsic bulk topological properties of spinful 3D insulators. We discover that helical HOTIs realize one of three spin-resolved phases with distinct responses that are quantitatively robust to large deformations of the bulk spin-orbital texture: 3D quantum spin Hall insulators (QSHIs), “spin-Weyl” semimetals, and $${{{{{{{\mathcal{T}}}}}}}}$$
T
-doubled axion insulator (T-DAXI) states with nontrivial partial axion angles indicative of a 3D spin-magnetoelectric bulk response and half-quantized 2D TI surface states originating from a partial parity anomaly. Using ab-initio calculations, we demonstrate that β-MoTe2 realizes a spin-Weyl state and that α-BiBr hosts both 3D QSHI and T-DAXI regimes.
High-speed and energy-efficient non-volatile silicon photonic memory based on heterogeneously integrated memresonator
Authors: Tossoun Bassem , Liang Di , Cheung Stanley , Fang Zhuoran , Sheng Xia , Strachan John Paul , Beausoleil Raymond G. 
Published: January 2024

AbstractRecently, interest in programmable photonics integrated circuits has grown as a potential hardware framework for deep neural networks, quantum computing, and field programmable arrays (FPGAs). However, these circuits are constrained by the limited tuning speed and large power consumption of the phase shifters used. In this paper, we introduce the memresonator, a metal-oxide memristor heterogeneously integrated with a microring resonator, as a non-volatile silicon photonic phase shifter. These devices are capable of retention times of 12 hours, switching voltages lower than 5 V, and an endurance of 1000 switching cycles. Also, these memresonators have been switched using 300 ps long voltage pulses with a record low switching energy of 0.15 pJ. Furthermore, these memresonators are fabricated on a heterogeneous III-V-on-Si platform capable of integrating a rich family of active and passive optoelectronic devices directly on-chip to enable in-memory photonic computing and further advance the scalability of integrated photonic processors.
Site-specific metal-support interaction to switch the activity of Ir single atoms for oxygen evolution reaction
Authors: Wei Jie , Tang Hua , Sheng Li , Wang Ruyang , Fan Minghui , Wan Jiale , Wu Yuheng , Zhang Zhirong , Zhou Shiming , Zeng Jie 
Published: January 2024

AbstractThe metal-support interactions (MSI) could greatly determine the electronic properties of single-atom catalysts, thus affecting the catalytic performance. However, the typical approach to regulating MSI usually suffers from interference of the variation of supports or sacrificing the stability of catalysts. Here, we effectively regulate the site-specific MSI of Ir single atoms anchored on Ni layered double hydroxide through an electrochemical deposition strategy. Cathodic deposition drives Ir atoms to locate at three-fold facial center cubic hollow sites with strong MSI, while anodic deposition drives Ir atoms to deposit onto oxygen vacancy sites with weak MSI. The mass activity and intrinsic activity of Ir single-atom catalysts with strong MSI towards oxygen evolution reaction are 19.5 and 5.2 times that with weak MSI, respectively. Mechanism study reveals that the strong MSI between Ir atoms and the support stimulates the activity of Ir sites by inducing the switch of active sites from Ni sites to Ir sites and optimizes the adsorption strength of intermediates, thereby enhancing the activity.