bluuebunny/crossref_metadata_2025_split huggingface dataset:
Balancing Sediment Connectivity and Energy Production via Optimized Reservoir Sediment Management Strategies
Authors: Tangi M. , Bizzi S. , Schmitt R. , Castelletti A. 
Published: June 2023

AbstractSediment connectivity plays a fundamental role in sustaining ecosystem goods and services in fluvial systems, including hydropower production. Dams alter the natural processes of sediment transport by trapping sediment and reshaping downstream hydrology and geomorphology. Due to these processes' interconnected nature, dams' impacts extend in time and space beyond the dam site to the entire river system. System‐scale approaches to reduce dam impacts commonly only consider dam siting, overlooking the potential of sediment management strategies integrated into the dam operations to offer more flexible solutions for mitigation. Herein, we contribute a sediment routing model (D‐CASCADE) to assess the impacts of reservoirs and their management strategies on river sediment connectivity. D‐CASCADE is applied to the 3S river system, a tributary of the Mekong River, a hotspot of potential dams in the Lower Mekong. We analyze three dam development portfolios. The effect of reservoir management is examined by assessing daily sediment delivery with specific dam release strategies. Model results predict sediment yield to the Mekong to reduce by 31%–60%. Finally, we explore trade‐offs between hydropower generation and sediment connectivity across cascades of multiple reservoirs. Results show that repeated flushing operations during the early wet season could significantly increase sediment delivery with minimal (max 6%) hydropower losses. While poor trade‐offs between sediment and hydropower have been locked‐in in the Mekong, our results highlight the potential of including sediment connectivity models in multi‐objective decision‐making frameworks to devise integrated water and sediment management strategies that mitigate connectivity disruptions while minimizing losses in other sectors.
Final results of DESTINY-CRC01 investigating trastuzumab deruxtecan in patients with HER2-expressing metastatic colorectal cancer
Authors: Yoshino Takayuki , Di Bartolomeo Maria , Raghav Kanwal , Masuishi Toshiki , Loupakis Fotios , Kawakami Hisato , Yamaguchi Kensei , Nishina Tomohiro , Wainberg Zev , Elez Elena , Rodriguez Javier , Fakih Marwan , Ciardiello Fortunato , Saxena Kapil , Kobayashi Kojiro , Bako Emarjola , Okuda Yasuyuki , Meinhardt Gerold , Grothey Axel , Siena Salvatore ,   DESTINY-CRC01 investigators, Di Bartolomeo Maria 
Published: June 2023

AbstractDESTINY-CRC01 (NCT03384940) was a multicenter, open-label, phase 2 trial assessing the efficacy and safety of trastuzumab deruxtecan (T-DXd) in patients with HER2-expressing metastatic colorectal cancer (mCRC) that progressed after ≥2 prior regimens; results of the primary analysis are published. Patients received T-DXd 6.4 mg/kg every 3 weeks and were assigned to either: cohort A (HER2-positive, immunohistochemistry [IHC] 3+ or IHC 2+/in situ hybridization [ISH]+), cohort B (IHC 2+/ISH−), or cohort C (IHC 1+). Primary endpoint was objective response rate (ORR) by independent central review in cohort A. Secondary endpoints included ORR (cohorts B and C), duration of response, disease control rate, progression-free survival, overall survival, pharmacokinetics, and safety of T-DXd. 86 patients were enrolled (53 in cohort A, 15 in cohort B, and 18 in cohort C). Results of the primary analysis are published, reporting an ORR of 45.3% in cohort A. Here, we report the final results. No responses occurred in cohorts B or C. Median progression-free survival, overall survival, and duration of response were 6.9, 15.5, and 7.0 months, respectively. Overall serum exposure (cycle 1) of T-DXd, total anti-HER2 antibody, and DXd were similar regardless of HER2 status. Most common grade ≥3 treatment-emergent adverse events were decreased neutrophil count and anemia. Adjudicated drug-related interstitial lung disease/pneumonitis occurred in 8 patients (9.3%). These findings support the continued exploration of T-DXd in HER2-positive mCRC.
Electrostatic control of the proximity effect in the bulk of semiconductor-superconductor hybrids
Authors: van Loo Nick , Mazur Grzegorz P. , Dvir Tom , Wang Guanzhong , Dekker Robin C. , Wang Ji-Yin , Lemang Mathilde , Sfiligoj Cristina , Bordin Alberto , van Driel David , Badawy Ghada , Gazibegovic Sasa , Bakkers Erik P. A. M. , Kouwenhoven Leo P. 
Published: June 2023

AbstractThe proximity effect in semiconductor-superconductor nanowires is expected to generate an induced gap in the semiconductor. The magnitude of this induced gap, together with the semiconductor properties like spin-orbit coupling and g-factor, depends on the coupling between the materials. It is predicted that this coupling can be adjusted through the use of electric fields. We study this phenomenon in InSb/Al/Pt hybrids using nonlocal spectroscopy. We show that these hybrids can be tuned such that the semiconductor and superconductor are strongly coupled. In this case, the induced gap is similar to the superconducting gap in the Al/Pt shell and closes only at high magnetic fields. In contrast, the coupling can be suppressed which leads to a strong reduction of the induced gap and critical magnetic field. At the crossover between the strong-coupling and weak-coupling regimes, we observe the closing and reopening of the induced gap in the bulk of a nanowire. Contrary to expectations, it is not accompanied by the formation of zero-bias peaks in the local conductance spectra. As a result, this cannot be attributed conclusively to the anticipated topological phase transition and we discuss possible alternative explanations.
The supercurrent diode effect and nonreciprocal paraconductivity due to the chiral structure of nanotubes
Authors: He James Jun , Tanaka Yukio , Nagaosa Naoto 
Published: June 2023

AbstractThe phenomenon that critical supercurrents along opposite directions become unequal is called the supercurrent diode effect (SDE). It has been observed in various systems and can often be understood by combining spin-orbit coupling and Zeeman field, which break the spatial-inversion and time-reversal symmetries, respectively. Here, we theoretically investigate another mechanism of breaking these symmetries and predict the existence of the SDE in chiral nanotubes without spin-orbit coupling. The symmetries are broken by the chiral structure and a magnetic flux through the tube. With a generalized Ginzburg-Landau theory, we obtain the main features of the SDE in its dependence on system parameters. We further show that the same Ginzburg-Landau free energy leads to another important manifestation of the nonreciprocity in superconducting systems, i.e., the nonreciprocal paraconductivity (NPC) slightly above the transition temperature. Our study suggests a new class of realistic platforms to investigate nonreciprocal properties of superconducting materials. It also provides a theoretical link between the SDE and the NPC, which were often studied separately.
Myeloid cell infiltration in skeletal muscle after combined hindlimb unloading and radiation exposure in mice
Authors: Emanuelsson Eric B. , Baselet Bjorn , Neefs Mieke , Baatout Sarah , Proesmans Brit , Daenen Lisa , Sundberg Carl Johan , Rundqvist Helene , Fernandez-Gonzalo Rodrigo 
Published: June 2023

AbstractThe skeletal muscle and the immune system are heavily affected by the space environment. The crosstalk between these organs, although established, is not fully understood. This study determined the nature of immune cell changes in the murine skeletal muscle following (hindlimb) unloading combined with an acute session of irradiation (HLUR). Our findings show that 14 days of HLUR induces a significant increase of myeloid immune cell infiltration in skeletal muscle.
A metal-poor star with abundances from a pair-instability supernova
Authors: Xing Qian-Fan , Zhao Gang , Liu Zheng-Wei , Heger Alexander , Han Zhan-Wen , Aoki Wako , Chen Yu-Qin , Ishigaki Miho N. , Li Hai-Ning , Zhao Jing-Kun 
Published: June 2023

AbstractThe most massive and shortest-lived stars dominate the chemical evolution of the pre-galactic era. On the basis of numerical simulations, it has long been speculated that the mass of such first-generation stars was up to several hundred solar masses1–4. The very massive first-generation stars with a mass range from 140 to 260 solar masses are predicted to enrich the early interstellar medium through pair-instability supernovae (PISNe)5. Decades of observational efforts, however, have not been able to uniquely identify the imprints of such very massive stars on the most metal-poor stars in the Milky Way6,7. Here we report the chemical composition of a very metal-poor (VMP) star with extremely low sodium and cobalt abundances. The sodium with respect to iron in this star is more than two orders of magnitude lower than that of the Sun. This star exhibits very large abundance variance between the odd- and even-charge-number elements, such as sodium/magnesium and cobalt/nickel. Such peculiar odd–even effect, along with deficiencies of sodium and α elements, are consistent with the prediction of primordial pair-instability supernova (PISN) from stars more massive than 140 solar masses. This provides a clear chemical signature indicating the existence of very massive stars in the early universe.
Epigenetic dysregulation from chromosomal transit in micronuclei
Authors: Agustinus Albert S. , Al-Rawi Duaa , Dameracharla Bhargavi , Raviram Ramya , Jones Bailey S. C. L. , Stransky Stephanie , Scipioni Lorenzo , Luebeck Jens , Di Bona Melody , Norkunaite Danguole , Myers Robert M. , Duran Mercedes , Choi Seongmin , Weigelt Britta , Yomtoubian Shira , McPherson Andrew , Toufektchan Eléonore , Keuper Kristina , Mischel Paul S. , Mittal Vivek , Shah Sohrab P. , Maciejowski John , Storchova Zuzana , Gratton Enrico , Ly Peter , Landau Dan , Bakhoum Mathieu F. , Koche Richard P. , Sidoli Simone , Bafna Vineet , David Yael , Bakhoum Samuel F. 
Published: June 2023

AbstractChromosomal instability (CIN) and epigenetic alterations are characteristics of advanced and metastatic cancers1–4, but whether they are mechanistically linked is unknown. Here we show that missegregation of mitotic chromosomes, their sequestration in micronuclei5,6and subsequent rupture of the micronuclear envelope7profoundly disrupt normal histone post-translational modifications (PTMs), a phenomenon conserved across humans and mice, as well as in cancer and non-transformed cells. Some of the changes in histone PTMs occur because of the rupture of the micronuclear envelope, whereas others are inherited from mitotic abnormalities before the micronucleus is formed. Using orthogonal approaches, we demonstrate that micronuclei exhibit extensive differences in chromatin accessibility, with a strong positional bias between promoters and distal or intergenic regions, in line with observed redistributions of histone PTMs. Inducing CIN causes widespread epigenetic dysregulation, and chromosomes that transit in micronuclei experience heritable abnormalities in their accessibility long after they have been reincorporated into the primary nucleus. Thus, as well as altering genomic copy number, CIN promotes epigenetic reprogramming and heterogeneity in cancer.
Differentiation of retroperitoneal paragangliomas and schwannomas based on computed tomography radiomics
Authors: Cao Yuntai , Wang Zhan , Ren Jialiang , Liu Wencun , Da Huiwen , Yang Xiaotong , Bao Haihua 
Published: June 2023

AbstractThe purpose of this study was to differentiate the retroperitoneal paragangliomas and schwannomas using computed tomography (CT) radiomics. This study included 112 patients from two centers who pathologically confirmed retroperitoneal pheochromocytomas and schwannomas and underwent preoperative CT examinations. Radiomics features of the entire primary tumor were extracted from non-contrast enhancement (NC), arterial phase (AP) and venous phase (VP) CT images. The least absolute shrinkage and selection operator method was used to screen out key radiomics signatures. Radiomics, clinical and clinical-radiomics combined models were built to differentiate the retroperitoneal paragangliomas and schwannomas. Model performance and clinical usefulness were evaluated by receiver operating characteristic curve, calibration curve and decision curve. In addition, we compared the diagnostic accuracy of radiomics, clinical and clinical-radiomics combined models with radiologists for pheochromocytomas and schwannomas in the same set of data. Three NC, 4 AP, and 3 VP radiomics features were retained as the final radiomics signatures for differentiating the paragangliomas and schwannomas. The CT characteristics CT attenuation value of NC and the enhancement magnitude at AP and VP were found to be significantly different statistically (P < 0.05). The NC, AP, VP, Radiomics and clinical models had encouraging discriminative performance. The clinical-radiomics combined model that combined radiomics signatures and clinical characteristics showed excellent performance, with an area under curve (AUC) values were 0.984 (95% CI 0.952–1.000) in the training cohort, 0.955 (95% CI 0.864–1.000) in the internal validation cohort and 0.871 (95% CI 0.710–1.000) in the external validation cohort. The accuracy, sensitivity and specificity were 0.984, 0.970 and 1.000 in the training cohort, 0.960, 1.000 and 0.917 in the internal validation cohort and 0.917, 0.923 and 0.818 in the external validation cohort, respectively. Additionally, AP, VP, Radiomics, clinical and clinical-radiomics combined models had a higher diagnostic accuracy for pheochromocytomas and schwannomas than the two radiologists. Our study demonstrated the CT-based radiomics models has promising performance in differentiating the paragangliomas and schwannomas.
Stochastic optimization of a uranium oxide reaction mechanism using plasma flow reactor measurements
Authors: Finko Mikhail , Koroglu Batikan , Rodriguez Kate E. , Rose Timothy P. , Crowhurst Jonathan C. , Curreli Davide , Radousky Harry B. , Knight Kim B. 
Published: June 2023

AbstractIn this work, a coupled Monte Carlo Genetic Algorithm (MCGA) approach is used to optimize a gas phase uranium oxide reaction mechanism based on plasma flow reactor (PFR) measurements. The PFR produces a steady Ar plasma containing U, O, H, and N species with high temperature regions (3000–5000 K) relevant to observing UO formation via optical emission spectroscopy. A global kinetic treatment is used to model the chemical evolution in the PFR and to produce synthetic emission signals for direct comparison with experiments. The parameter space of a uranium oxide reaction mechanism is then explored via Monte Carlo sampling using objective functions to quantify the model-experiment agreement. The Monte Carlo results are subsequently refined using a genetic algorithm to obtain an experimentally corroborated set of reaction pathways and rate coefficients. Out of 12 reaction channels targeted for optimization, four channels are found to be well constrained across all optimization runs while another three channels are constrained in select cases. The optimized channels highlight the importance of the OH radical in oxidizing uranium in the PFR. This study comprises a first step toward producing a comprehensive experimentally validated reaction mechanism for gas phase uranium molecular species formation.
Recycling of both resin and fibre from wind turbine blade waste via small molecule-assisted dissolution
Authors: Muzyka Roksana , Sobek Szymon , Korytkowska-Wałach Anna , Drewniak Łukasz , Sajdak Marcin 
Published: June 2023

AbstractWind energy has significant growth potential and applicability on a global scale, but approximately 2.4% of wind turbine blades must be decommissioned annually. The majority of blade components can be recycled; however, wind blades are rarely recycled. In the present study, an alternative method was presented involving a small molecule-assisted technique based on a dynamic reaction that dissolves waste composite materials containing ester groups to recycle end-of-life wind turbine blades. This effective process requires temperatures below 200 °C, and the major component, i.e., resin, can be easily dissolved. This method can be applied to recycle composite materials, such as wind turbine blades and carbon fibre composites comprising fibres and resins. Depending on the waste, up to 100% of the resin degradation yield can be achieved. The solution used for the recycling process may be reused multiple times and can be reused to obtain resin-based components and create a closed loop for this type of material.
ATP6AP2 is robustly expressed in pancreatic β cells and neuroendocrine tumors, and plays a role in maintaining cellular viability
Authors: Taguchi Tomomi , Kimura Kaori , Suzuki Agena , Fujishima Rei , Shimizu Naoya , Hoshiyama Ayako , Masaki Tsuguto , Inoue Mitsuko , Kato Yukiko , Satomi Takebe , Takano Koji , Imada Tasuku , Sasaki Shugo , Miyatsuka Takeshi 
Published: June 2023

AbstractATP6AP2, also known as (pro)renin receptor, has been shown to be expressed in several tissues including pancreatic β cells. Whereas ATP6AP2 plays an important role in regulating insulin secretion in mouse pancreatic β cells, the expression profiles and roles of ATP6AP2 in human pancreatic endocrine cells and neuroendocrine tumor cells remain unclear. Here in this study, we investigated the expression profiles of ATP6AP2 in pancreatic endocrine cells, and found that ATP6AP2 is robustly expressed in pancreatic insulinoma cells as well as in normal β cells. Although ATP6AP2 was also expressed in low-grade neuroendocrine tumors, it was not or faintly detected in intermediate- and high-grade neuroendocrine tumors. Knockdown experiments of the Atp6ap2 gene in rat insulinoma-derived INS-1 cells demonstrated decreased cell viability accompanied by a significant increase in apoptotic cells. Taken together, these findings suggest that ATP6AP2 plays a role in maintaining cellular homeostasis in insulinoma cells, which could lead to possible therapeutic approaches for endocrine tumors.
DEDTI versus IEDTI: efficient and predictive models of drug-target interactions
Authors: Zabihian Arash , Sayyad Faeze Zakaryapour , Hashemi Seyyed Morteza , Shami Tanha Reza , Hooshmand Mohsen , Gharaghani Sajjad 
Published: June 2023

AbstractDrug repurposing is an active area of research that aims to decrease the cost and time of drug development. Most of those efforts are primarily concerned with the prediction of drug-target interactions. Many evaluation models, from matrix factorization to more cutting-edge deep neural networks, have come to the scene to identify such relations. Some predictive models are devoted to the prediction’s quality, and others are devoted to the efficiency of the predictive models, e.g., embedding generation. In this work, we propose new representations of drugs and targets useful for more prediction and analysis. Using these representations, we propose two inductive, deep network models of IEDTI and DEDTI for drug-target interaction prediction. Both of them use the accumulation of new representations. The IEDTI takes advantage of triplet and maps the input accumulated similarity features into meaningful embedding corresponding vectors. Then, it applies a deep predictive model to each drug-target pair to evaluate their interaction. The DEDTI directly uses the accumulated similarity feature vectors of drugs and targets and applies a predictive model on each pair to identify their interactions. We have done a comprehensive simulation on the DTINet dataset as well as gold standard datasets, and the results show that DEDTI outperforms IEDTI and the state-of-the-art models. In addition, we conduct a docking study on new predicted interactions between two drug-target pairs, and the results confirm acceptable drug-target binding affinity between both predicted pairs.
Preserving privacy in surgical video analysis using a deep learning classifier to identify out-of-body scenes in endoscopic videos
Authors: Lavanchy Joël L. , Vardazaryan Armine , Mascagni Pietro ,   AI4SafeChole Consortium, Laracca Giovanni Guglielmo , Guerriero Ludovica , Spota Andrea , Fiorillo Claudio , Quero Giuseppe , Alfieri Segio , Baldari Ludovica , Cassinotti Elisa , Boni Luigi , Cuccurullo Diego , Costamagna Guido , Dallemagne Bernard , Mutter Didier , Padoy Nicolas 
Published: June 2023

AbstractSurgical video analysis facilitates education and research. However, video recordings of endoscopic surgeries can contain privacy-sensitive information, especially if the endoscopic camera is moved out of the body of patients and out-of-body scenes are recorded. Therefore, identification of out-of-body scenes in endoscopic videos is of major importance to preserve the privacy of patients and operating room staff. This study developed and validated a deep learning model for the identification of out-of-body images in endoscopic videos. The model was trained and evaluated on an internal dataset of 12 different types of laparoscopic and robotic surgeries and was externally validated on two independent multicentric test datasets of laparoscopic gastric bypass and cholecystectomy surgeries. Model performance was evaluated compared to human ground truth annotations measuring the receiver operating characteristic area under the curve (ROC AUC). The internal dataset consisting of 356,267 images from 48 videos and the two multicentric test datasets consisting of 54,385 and 58,349 images from 10 and 20 videos, respectively, were annotated. The model identified out-of-body images with 99.97% ROC AUC on the internal test dataset. Mean ± standard deviation ROC AUC on the multicentric gastric bypass dataset was 99.94 ± 0.07% and 99.71 ± 0.40% on the multicentric cholecystectomy dataset, respectively. The model can reliably identify out-of-body images in endoscopic videos and is publicly shared. This facilitates privacy preservation in surgical video analysis.
High spin current density in gate-tunable spin-valves based on graphene nanoribbons
Authors: Wang Chun-Pu , Cheng Shih-Hung , Hsueh Wen-Jeng 
Published: June 2023

AbstractThe usage of two-dimensional (2D) materials will be very advantageous for many developing spintronic device designs, providing a superior method of managing spin. Non-volatile memory technologies, particularly magnetic random-access memories (MRAMs), characterized by 2D materials are the goal of the effort. A sufficiently large spin current density is indispensable for the writing mode of MRAMs to switch states. How to attain spin current density beyond critical values around 5 MA/cm2 in 2D materials at room temperature is the greatest obstacle to overcome. Here, we first theoretically propose a spin valve based on graphene nanoribbons (GNRs) to generate a huge spin current density at room temperature. The spin current density can achieve the critical value with the help of tunable gate voltage. The highest spin current density can reach 15 MA/cm2 by adjusting the band gap energy of GNRs and exchange strength in our proposed gate-tunable spin-valve. Also, ultralow writing power can be obtained, successfully overcoming the difficulties traditional magnetic tunnel junction-based MRAMs have faced. Furthermore, the proposed spin-valve meets the reading mode criteria and the MR ratios are always higher than 100%. These results may open the feasibility avenues for spin logic devices based on 2D materials.