bluuebunny/crossref_metadata_2025_split huggingface dataset:
Developing a class of dual atom materials for multifunctional catalytic reactions
Authors: Wang Xingkun , Xu Liangliang , Li Cheng , Zhang Canhui , Yao Hanxu , Xu Ren , Cui Peixin , Zheng Xusheng , Gu Meng , Lee Jinwoo , Jiang Heqing , Huang Minghua 
Published: November 2023

AbstractDual atom catalysts, bridging single atom and metal/alloy nanoparticle catalysts, offer more opportunities to enhance the kinetics and multifunctional performance of oxygen reduction/evolution and hydrogen evolution reactions. However, the rational design of efficient multifunctional dual atom catalysts remains a blind area and is challenging. In this study, we achieved controllable regulation from Co nanoparticles to CoN4 single atoms to Co2N5 dual atoms using an atomization and sintering strategy via an N-stripping and thermal-migrating process. More importantly, this strategy could be extended to the fabrication of 22 distinct dual atom catalysts. In particular, the Co2N5 dual atom with tailored spin states could achieve ideally balanced adsorption/desorption of intermediates, thus realizing superior multifunctional activity. In addition, it endows Zn-air batteries with long-term stability for 800 h, allows water splitting to continuously operate for 1000 h, and can enable solar-powered water splitting systems with uninterrupted large-scale hydrogen production throughout day and night. This universal and scalable strategy provides opportunities for the controlled design of efficient multifunctional dual atom catalysts in energy conversion technologies.
Spatially resolved mapping of proteome turnover dynamics with subcellular precision
Authors: Yuan Feng , Li Yi , Zhou Xinyue , Meng Peiyuan , Zou Peng 
Published: November 2023

AbstractCellular activities are commonly associated with dynamic proteomic changes at the subcellular level. Although several techniques are available to quantify whole-cell protein turnover dynamics, such measurements often lack sufficient spatial resolution at the subcellular level. Herein, we report the development of prox-SILAC method that combines proximity-dependent protein labeling (APEX2/HRP) with metabolic incorporation of stable isotopes (pulse-SILAC) to map newly synthesized proteins with subcellular spatial resolution. We apply prox-SILAC to investigate proteome dynamics in the mitochondrial matrix and the endoplasmic reticulum (ER) lumen. Our analysis reveals a highly heterogeneous distribution in protein turnover dynamics within macromolecular machineries such as the mitochondrial ribosome and respiratory complexes I-V, thus shedding light on their mechanism of hierarchical assembly. Furthermore, we investigate the dynamic changes of ER proteome when cells are challenged with stress or undergoing stimulated differentiation, identifying subsets of proteins with unique patterns of turnover dynamics, which may play key regulatory roles in alleviating stress or promoting differentiation. We envision that prox-SILAC could be broadly applied to profile protein turnover at various subcellular compartments, under both physiological and pathological conditions.
Multiple E3 ligases control tankyrase stability and function
Authors: Perrard Jerome , Smith Susan 
Published: November 2023

AbstractTankyrase 1 and 2 are ADP-ribosyltransferases that catalyze formation of polyADP-Ribose (PAR) onto themselves and their binding partners. Tankyrase protein levels are regulated by the PAR-binding E3 ligase RNF146, which promotes K48-linked polyubiquitylation and proteasomal degradation of tankyrase and its partners. We identified a novel interaction between tankyrase and a distinct class of E3 ligases: the RING-UIM (Ubiquitin-Interacting Motif) family. We show that RNF114 and RNF166 bind and stabilize monoubiquitylated tankyrase and promote K11-linked diubiquitylation. This action competes with RNF146-mediated degradation, leading to stabilization of tankyrase and its binding partner, Angiomotin, a cancer cell signaling protein. Moreover, we identify multiple PAR-binding E3 ligases that promote ubiquitylation of tankyrase and induce stabilization or degradation. Discovery of K11 ubiquitylation that opposes degradation, along with identification of multiple PAR-binding E3 ligases that ubiquitylate tankyrase, provide insights into mechanisms of tankyrase regulation and may offer additional uses for tankyrase inhibitors in cancer therapy.
Observation of aligned dipoles and angular chromism of exciplexes in organic molecular heterostructures
Authors: Lee Sang-hun , Kim Taek Joon , Lee Eunji , Kwon Dayeong , Kim Jeongyong , Joo Jinsoo 
Published: November 2023

AbstractThe dipole characteristics of Frenkel excitons and charge-transfer excitons between donor and acceptor molecules in organic heterostructures such as exciplexes are important in organic photonics and optoelectronics. For the bilayer of the organic donor 4,4′,4′′-tris[(3-methylphenyl)phenylamino]triphenylamine and acceptor 2,4,6-tris(biphenyl-3-yl)-1,3,5-triazine molecules, the exciplexes form aligned dipoles perpendicular to the Frenkel excitons, as observed in back focal plane photoluminescence images. The angular chromism of exciplexes observed in the 100 meV range indicates possible delocalization and angle-sensing photonic applications. The blue shift of the peak position and increase in the linewidth of photoluminescene spectra with increasing excitation power are caused by the repulsive aligned exciplex dipole moments with a long lifetime (4.65 μs). Electroluminescence spectra of the exciplex from organic light-emitting diodes using the bilayer are blue-shifted with increasing bias, suggesting unidirectional alignment of the exciplex dipole moments. The observation of exciplex dipole moment alignments across molecular interfaces can facilitate the controlled coupling of exciton species and increase efficiency of organic light-emitting diodes.
Reversed asymmetric warming of sub-diurnal temperature over land during recent decades
Authors: Zhong Ziqian , He Bin , Chen Hans W. , Chen Deliang , Zhou Tianjun , Dong Wenjie , Xiao Cunde , Xie Shang-ping , Song Xiangzhou , Guo Lanlan , Ding Ruiqiang , Zhang Lixia , Huang Ling , Yuan Wenping , Hao Xingming , Ji Duoying , Zhao Xiang 
Published: November 2023

AbstractIn the latter half of the twentieth century, a significant climate phenomenon “diurnal asymmetric warming” emerged, wherein global land surface temperatures increased more rapidly during the night than during the day. However, recent episodes of global brightening and regional droughts and heatwaves have brought notable alterations to this asymmetric warming trend. Here, we re-evaluate sub-diurnal temperature patterns, revealing a substantial increase in the warming rates of daily maximum temperatures (Tmax), while daily minimum temperatures have remained relatively stable. This shift has resulted in a reversal of the diurnal warming trend, expanding the diurnal temperature range over recent decades. The intensified Tmax warming is attributed to a widespread reduction in cloud cover, which has led to increased solar irradiance at the surface. Our findings underscore the urgent need for enhanced scrutiny of recent temperature trends and their implications for the wider earth system.
Mechanism of selective recognition of Lys48-linked polyubiquitin by macrocyclic peptide inhibitors of proteasomal degradation
Authors: Lemma Betsegaw , Zhang Di , Vamisetti Ganga B. , Wentz Bryan G. , Suga Hiroaki , Brik Ashraf , Lubkowski Jacek , Fushman David 
Published: November 2023

AbstractPost-translational modification of proteins with polyubiquitin chains is a critical cellular signaling mechanism in eukaryotes with implications in various cellular states and processes. Unregulated ubiquitin-mediated protein degradation can be detrimental to cellular homeostasis, causing numerous diseases including cancers. Recently, macrocyclic peptides were developed that selectively target long Lysine-48-linked polyubiquitin chains (tetra-ubiquitin) to inhibit ubiquitin-proteasome system, leading to attenuation of tumor growth in vivo. However, structural determinants of the chain length and linkage selectivity by these cyclic peptides remained unclear. Here, we uncover the mechanism underlying cyclic peptide’s affinity and binding selectivity by combining X-ray crystallography, solution NMR, and biochemical studies. We found that the peptide engages three consecutive ubiquitins that form a ring around the peptide and determined requirements for preferential selection of a specific trimer moiety in longer polyubiquitin chains. The structural insights gained from this work will guide the development of next-generation cyclic peptides with enhanced anti-cancer activity.
A single cell genomics atlas of the Drosophila larval eye reveals distinct photoreceptor developmental timelines
Authors: Bollepogu Raja Komal Kumar , Yeung Kelvin , Shim Yoon-Kyung , Li Yumei , Chen Rui , Mardon Graeme 
Published: November 2023

AbstractTheDrosophilaeye is a powerful model system to study the dynamics of cell differentiation, cell state transitions, cell maturation, and pattern formation. However, a high-resolution single cell genomics resource that accurately profiles all major cell types of the larval eye disc and their spatiotemporal relationships is lacking. Here, we report transcriptomic and chromatin accessibility data for all known cell types in the developing eye. Photoreceptors appear as strands of cells that represent their dynamic developmental timelines. As photoreceptor subtypes mature, they appear to assume a common transcriptomic profile that is dominated by genes involved in axon function. We identify cell type maturation genes, enhancers, and potential regulators, as well as genes with distinct R3 or R4 photoreceptor specific expression. Finally, we observe that the chromatin accessibility between cones and photoreceptors is distinct. These single cell genomics atlases will greatly enhance the power of theDrosophilaeye as a model system.
Probabilistic computing with NbOx metal-insulator transition-based self-oscillatory pbit
Authors: Rhee Hakseung , Kim Gwangmin , Song Hanchan , Park Woojoon , Kim Do Hoon , In Jae Hyun , Lee Younghyun , Kim Kyung Min 
Published: November 2023

AbstractEnergy-based computing is a promising approach for addressing the rising demand for solving NP-hard problems across diverse domains, including logistics, artificial intelligence, cryptography, and optimization. Probabilistic computing utilizing pbits, which can be manufactured using the semiconductor process and seamlessly integrated with conventional processing units, stands out as an efficient candidate to meet these demands. Here, we propose a novel pbit unit using an NbOx volatile memristor-based oscillator capable of generating probabilistic bits in a self-clocking manner. The noise-induced metal-insulator transition causes the probabilistic behavior, which can be effectively modeled using a multi-noise-induced stochastic process around the metal-insulator transition temperature. We demonstrate a memristive Boltzmann machine based on our proposed pbit and validate its feasibility by solving NP-hard problems. Furthermore, we propose a streamlined operation methodology that considers the autocorrelation of individual bits, enabling energy-efficient and high-performance probabilistic computing.
The EPOS multi-disciplinary Data Portal for integrated access to solid Earth science datasets
Authors: Bailo Daniele , Paciello Rossana , Michalek Jan , Cocco Massimo , Freda Carmela , Jeffery Keith , Atakan Kuvvet 
Published: November 2023

AbstractThe European Plate Observing System (EPOS) is a long-term initiative aimed at integrating research infrastructures for solid Earth science in Europe. EPOS provides a sustainable, multidisciplinary user-oriented platform - the EPOS Data Portal - that facilitates data integration, access, use, and re-use, while adhering to the FAIR principles. The paper describes the key governance, community building, and technical aspects for achieving multidisciplinary data integration through the portal. It also outlines the key portal features for aggregating approximately 250 data sources from more than ten different scientific communities. The main architectural concepts underpinning the portal, namely the rich-metadata, the service-driven data provision, and the usage of semantics, are outlined. The paper discusses the challenges encountered during the creation of the portal, describes the community engagement process, and highlights the benefits to the scientific community and society. Future work includes expanding portal functionalities to include data analysis, processing, and visualization and releasing the portal as an open-source software package.
Prophylactic treatment can modify vascular risk biomarkers in high-frequency episodic and chronic migraine patients: a pilot study
Authors: González Mingot Cristina , Santos Lasaosa Sonia , Colàs Campàs Laura , Chilangua Canaval Laura , Gil Sánchez Anna , Brieva Ruiz Luis , Marzo Alonso María Cristina , Peralta Moncusi Silvia , Valls Marsal Joan , Cambray Carner Serafí , Purroy García Francisco 
Published: November 2023

AbstractTo evaluate whether preventive treatment can modify endothelial and oxidative biomarkers of vascular disease risk in patients with high-frequency episodic and chronic migraine. In this observational, prospective pilot study, 88 prophylactic treatment-naïve patients with episodic and chronic migraine and 56 healthy sex/age matched controls underwent ultrasonography exams and blood tests at baseline, and again in the migraine patients after 3 months’ treatment with metoprolol or topiramate. Biomarkers for endothelial function and oxidative stress were analyzed. At baseline, patients with migraine in the low-frequency episodic group had differences exclusively in nitrates 17.6 versus 27.33 µM; p = 0.046 compared to the controls. However, when comparing the group comprised of patients with high-frequency episodic migraine and chronic migraine versus controls, statistically significant differences appeared in hsCRP 2.68 versus 1.64 mg/dL; p = 0.049, vWF antigen (133% vs. 110%; p = 0.020, vWF activity (111% vs. 90%; p = 0.010) and isoprostane levels (181 vs. 238 µM; p = 0.05). Only in the chronic migraine subgroup did we found statistically significant differences in CIMT (0.60 vs. 0.54 mm; p = 0.042) which were significantly greater than in the controls. After treatment, patients who respond to preventive treatment exhibited significantly higher levels of nitrates (24.2–13.8 µM; p = 0.022) and nitrites (10.4–3.43 µM; p = 0.002) compared than non-responders. Moreover, biomarker levels improved in treatment-responsive patients with migraine; hsCRP levels decreased from 2.54 to 1.69 mg/dL (p < 0.05), vWF activity levels decreased from 124 to 103 IU/dL (p = 0.003) and prothrombin activity decreased from 1.01 to 0.93 (p = 0.01). These differences were also observed in the high-frequency and chronic migraine subgroup and reach statistical significance in the case of hsCRP, which decreased from 2.12 to 0.83 mg/dL (p = 0.048). Patients with migraines have differences in biomarker levels compared to controls, suggesting endothelial and oxidative dysfunction. The greatest differences in biomarker levels compared to controls are observed in migraine patients in the high-frequency and chronic migraine subgroups. Based on our results, preventive treatment is capable of modifying markers of endothelial dysfunction and oxidative stress in migraine patients, even in cases of chronic and high-frequency migraine.
Best practices for portfolio optimization by quantum computing, experimented on real quantum devices
Authors: Buonaiuto Giuseppe , Gargiulo Francesco , De Pietro Giuseppe , Esposito Massimo , Pota Marco 
Published: November 2023

AbstractIn finance, portfolio optimization aims at finding optimal investments maximizing a trade-off between return and risks, given some constraints. Classical formulations of this quadratic optimization problem have exact or heuristic solutions, but the complexity scales up as the market dimension increases. Recently, researchers are evaluating the possibility of facing the complexity scaling issue by employing quantum computing. In this paper, the problem is solved using the Variational Quantum Eigensolver (VQE), which in principle is very efficient. The main outcome of this work consists of the definition of the best hyperparameters to set, in order to perform Portfolio Optimization by VQE on real quantum computers. In particular, a quite general formulation of the constrained quadratic problem is considered, which is translated into Quadratic Unconstrained Binary Optimization by the binary encoding of variables and by including constraints in the objective function. This is converted into a set of quantum operators (Ising Hamiltonian), whose minimum eigenvalue is found by VQE and corresponds to the optimal solution. In this work, different hyperparameters of the procedure are analyzed, including different ansatzes and optimization methods by means of experiments on both simulators and real quantum computers. Experiments show that there is a strong dependence of solutions quality on the sufficiently sized quantum computer and correct hyperparameters, and with the best choices, the quantum algorithm run on real quantum devices reaches solutions very close to the exact one, with a strong convergence rate towards the classical solution, even without error-mitigation techniques. Moreover, results obtained on different real quantum devices, for a small-sized example, show the relation between the quality of the solution and the dimension of the quantum processor. Evidences allow concluding which are the best ways to solve real Portfolio Optimization problems by VQE on quantum devices, and confirm the possibility to solve them with higher efficiency, with respect to existing methods, as soon as the size of quantum hardware will be sufficiently high.
A prognostic model for ovarian neoplasms established by an integrated analysis of 1580 transcriptomic profiles
Authors: Hua Yanjiao , Cai Du , Shirley Cole Andrea , Mo Sien , Chen Ruyun , Gao Feng , Chen Fangying 
Published: November 2023

AbstractEven after debulking surgery combined with chemotherapy or new adjuvant chemotherapy paired with internal surgery, the average year of disease free survival in advanced ovarian cancer was approximately 1.7 years1. The development of a molecular predictor of early recurrence would allow for the identification of ovarian cancer (OC) patients with high risk of relapse. The Ovarian Cancer Disease Free Survival Predictor (ODFSP), a predictive model constructed from a special set of 1580 OC tumors in which gene expression was assessed using both microarray and sequencing platforms, was created by our team. To construct gene expression barcodes that were resistant to biases caused by disparate profiling platforms and batch effects, we employed a meta-analysis methodology that was based on the binary gene pair technique. We demonstrate that ODFSP is a reliable single-sample predictor of early recurrence (1 year or less) using the largest pool of OC transcriptome data sets available to date. The ODFSP model showed significantly high prognostic value for binary recurrence prediction unaffected by clinicopathologic factors, with a meta-estimate of the area under the receiver operating curve of 0.64 (P  =  4.6E-05) and a D-index (robust hazard ratio) of 1.67 (P  =  9.2E-06), respectively. GO analysis of ODFSP’s 2040 gene pairs (collapsed to 886 distinct genes) revealed the involvement in small molecular catabolic process, sulfur compound metabolic process, organic acid catabolic process, sulfur compound biosynthetic process, glycosaminoglycan metabolic process and aminometabolic process. Kyoto encyclopedia of genes and genomes pathway analysis of ODFSP’s signature genes identified prominent pathways that included cAMP signaling pathway and FoxO signaling pathway. By identifying individuals who might benefit from a more aggressive treatment plan or enrolment in a clinical trial but who will not benefit from standard surgery or chemotherapy, ODFSP could help with treatment decisions.
Environmental pressures and pesticide exposure associated with an increase in the share of plant-based foods in the diet
Authors: Kesse-Guyot Emmanuelle , Allès Benjamin , Brunin Joséphine , Langevin Brigitte , Fouillet Hélène , Dussiot Alison , Berthy Florine , Reuzé Anouk , Perraud Elie , Rebouillat Pauline , Touvier Mathilde , Hercberg Serge , Mariotti François , Lairon Denis , Pointereau Philippe , Baudry Julia 
Published: November 2023

AbstractDiets rich in plant-based foods are encouraged for human health and to preserve resources and the environment but the nutritional quality and safety of such diets is debated. This study aimed to model nutritionally adequate diets with increasing plant food content and to characterise the derived diets using a multicriteria approach including, nutrients intake, environmental pressures and exposure to pesticides. Using data of the NutriNet-Santé cohort (N = 29,413), we implemented stepwise optimization models to identified maximum plant-food content under nutritional constraints. Environmental indicators at the production level were derived from the DIALECTE database, and exposure to pesticide residues from plant food consumption was estimated using a contamination database. Plant-based foods contributed to 64.3% (SD = 10.6%) of energy intake in observed diets and may reach up to 95% in modelled diets without jeopardizing nutritional status. Compared to the observed situation, an increase in plant-based foods in the diets led to increases in soy-based products (+ 480%), dried fruits (+ 370%), legumes (+ 317%), whole grains (+ 251%), oils (+ 144%) and vegetables (+ 93%). Animal products decreased progressively until total eviction, except for beef (− 98%). Dietary quality (estimated using the Diet Quality Index Based on the Probability of Adequate Nutrient Intake) was improved (up to 17%) as well as GHGe (up to − 65%), energy demand (up to − 48%), and land occupation (− 56%) for production. Exposures to pesticides from plant-based foods were increased by 100% conventional production and to a much lesser extent by 100% organic production. This study shows that shifting to nutritionally-adequate plant-based diets requires an in-depth rearrangement of food groups’ consumption but allows a drastic reduction environmental impact. Increase exposure to pesticide residues and related risks can be mitigated by consuming foods produced with low pesticide input.