bluuebunny/crossref_metadata_2025_split huggingface dataset:
Responses of Phytoplankton Communities to Internal Waves in Oligotrophic Oceans
Authors: Ma Lingqi , Bai Xiaolin , Laws Edward A. , Xiao Wupeng , Guo Cui , Liu Xin , Chiang Kuo‐Ping , Gao Kunshan , Huang Bangqin 
Published: September 2023

AbstractUnderstanding the potential impacts of internal waves on phytoplankton communities in oligotrophic oceans remains an important research challenge. In this study, we elucidated the impact of internal waves on phytoplankton communities through a comprehensive 154‐hr time‐series of observations in the South China Sea (SCS). We identified distinctive variations in phytoplankton pigment biomass and composition across the upper, middle, and lower layers of the euphotic zone, which we attributed to the perturbations triggered by internal waves. Phytoplankton other than Prochlorococcus in the lower, nutrient‐replete layer likely benefitted from allochthonous nutrients introduced by internal waves, but their growth rates were constrained by light limitation, and their pigment biomass was held in check by microzooplankton grazing. In contrast, in the upper, nutrient‐depleted layer, the relative abundance of Prochlorococcus increased, likely because of the ammonium regenerated by zooplankton. The middle layer, characterized as the deep chlorophyll maximum layer, exhibited a dynamic equilibrium characterized by nutrient and light co‐limitation. This equilibrium resulted in high nitrate assimilation and growth by phytoplankton. The balancing of those rates by significant grazing losses maintained total chlorophyll a concentrations at a high level. Based on these findings, we proposed a three‐layer euphotic zone structure characterized by distinct physiological conditions, nutrient‐light dynamics, grazing pressure, and phytoplankton responses to internal waves. This three‐layer paradigm elucidated the intricate interplay between internal waves and phytoplankton communities and provided insights into the mechanisms that govern primary production and carbon cycling in oligotrophic oceanic ecosystems.
Extracellular high molecular weight α-synuclein oligomers induce cell death by disrupting the plasma membrane
Authors: Ito Naohito , Tsuji Mayumi , Adachi Naoki , Nakamura Shiro , Sarkar Avijite Kumer , Ikenaka Kensuke , Aguirre César , Kimura Atsushi Michael , Kiuchi Yuji , Mochizuki Hideki , Teplow David B. , Ono Kenjiro 
Published: September 2023

Abstractα-Synuclein (αS), the causative protein of Parkinson’s disease and other α-synucleinopathies, aggregates from a low molecular weight form (LMW-αS) to a high molecular weight αS oligomer (HMW-αSo). Aggregated αS accumulates intracellularly, induces intrinsic apoptosis, is released extracellularly, and appears to propagate disease through prion-like spreading. Whether extracellular αS aggregates are cytotoxic, damage cell wall, or induce cell death is unclear. We investigated cytotoxicity and cell death caused by HMW-αSo or LMW-αS. Extracellular HMW-αSo was more cytotoxic than LMW-αS and was a crucial factor for inducing plasma membrane damage and cell death. HMW-αSo induced reactive oxygen species production and phospholipid peroxidation in the membrane, thereby impairing calcium homeostasis and disrupting plasma membrane integrity. HMW-αSo also induced extrinsic apoptosis and cell death by activating acidic sphingomyelinase. Thus, as extracellular HMW-αSo causes neuronal injury and death via cellular transmission and direct plasma membrane damage, we propose an additional disease progression pathway for α-synucleinopathies.
Efficacy and complications of single-port thoracoscopic minimally invasive esophagectomy in esophageal squamous cell carcinoma: a single-center experience
Authors: Zheng Fei , Yang Jun , Zhang Jiulong , Li Jiancheng , Fang Weimin , Chen Mingqiu 
Published: September 2023

AbstractThe traditional surgical technique for esophageal cancer is mainly open esophagectomy. With the innovation of surgical instruments, it is necessary to re-optimize the minimally invasive surgery. Therefore, single-port thoracoscopic minimally invasive esophagectomy (SPTE) is an important direction of development. This study retrospectively analyzed 202 patients with esophageal squamous cell carcinoma undergoing SPTE. Surgical variables and postoperative complications were further evaluated. All procedures were performed using SPTE. The number of patients who received R0 resection was 201 (99.5%). The total number of resected lymph nodes during the whole operation was on average 32.01 ± 12.15, and the mean number of positive lymph nodes was 1.56 ± 2.51. In 170 cases (84.2%), intraoperative blood loss did not exceed 100 ml (ml), while 1 case had postoperative bleeding. Only 1 patient (0.5%) required reoperation after surgery. Postoperative complications included 42 cases of pneumonia (20.8%), 9 cases of anastomotic leak (4.5%), 7 cases of pleural effusion (3.8%), and 1 case (0.5%) of both pleural hemorrhage and acute gastrointestinal hemorrhagic ulcer. Besides, we also recorded the time to remove the drain tube, which averaged 9.13 ± 5.31 days. In our study, we confirmed that the application of SPTE in clinical practice is feasible, and that the postoperative complications are at a low level.
Decoupling of Arctic variability from the North Pacific in a warmer climate
Authors: Jahfer Sharif , Ha Kyung-Ja , Franzke Christian L. E. , Lee Sun-Seon , Rodgers Keith B. , Lee Dong-Eun 
Published: September 2023

AbstractThe sea level pressure variability in the North Pacific modulates the climate of the Arctic and surrounding continents, substantially impacting ecosystems and indigenous communities. Our analysis based on data from the CESM2 Large Ensemble and different Model Intercomparison Project datasets reveals that the interannual variability of Arctic surface air temperature (SAT) gradually decouples from the contemporaneous atmospheric conditions over the North Pacific as external forcing increases in intensity in the future. Future projections show that the North Pacific-Arctic relationship during the fall season consistently weakens in magnitude until the end of this century, and in the 22nd and 23rd centuries, the relationship is negligible throughout the year. We show that under increased greenhouse gas emissions, the regional heat fluxes extensively control the Arctic temperature variability, and the strength of the projected North Pacific-Arctic relationship is strongly dependent on the Arctic sea ice extent. Our results suggest that under future warming, a strong coupling of Arctic SAT with the underlying ocean and a weakening of the meridional pressure gradient driven by an enhanced rate of sea ice retreat will weaken the interannual footprint of North Pacific variability on Arctic SAT. Therefore, we propose that the alarming rate of sea-ice decline over recent decades and projected in the near future could accelerate the rate of decoupling. Further, we suggest that mitigation strategies for the Arctic should focus on regional mechanisms operating on interannual and seasonal timescales.
Structure of the human ATAD2 AAA+ histone chaperone reveals mechanism of regulation and inter-subunit communication
Authors: Cho Carol , Ganser Christian , Uchihashi Takayuki , Kato Koichi , Song Ji-Joon 
Published: September 2023

AbstractATAD2 is a non-canonical ATP-dependent histone chaperone and a major cancer target. Despite widespread efforts to design drugs targeting the ATAD2 bromodomain, little is known about the overall structural organization and regulation of ATAD2. Here, we present the 3.1 Å cryo-EM structure of human ATAD2 in the ATP state, showing a shallow hexameric spiral that binds a peptide substrate at the central pore. The spiral conformation is locked by an N-terminal linker domain (LD) that wedges between the seam subunits, thus limiting ATP-dependent symmetry breaking of the AAA+ ring. In contrast, structures of the ATAD2-histone H3/H4 complex show the LD undocked from the seam, suggesting that H3/H4 binding unlocks the AAA+ spiral by allosterically releasing the LD. These findings, together with the discovery of an inter-subunit signaling mechanism, reveal a unique regulatory mechanism for ATAD2 and lay the foundation for developing new ATAD2 inhibitors.
High-dimensional time-frequency entanglement in a singly-filtered biphoton frequency comb
Authors: Cheng Xiang , Chang Kai-Chi , Sarihan Murat Can , Mueller Andrew , Spiropulu Maria , Shaw Matthew D. , Korzh Boris , Faraon Andrei , Wong Franco N. C. , Shapiro Jeffrey H. , Wong Chee Wei 
Published: September 2023

AbstractHigh-dimensional quantum entanglement is a cornerstone for advanced technology enabling large-scale noise-tolerant quantum systems, fault-tolerant quantum computing, and distributed quantum networks. The recently developed biphoton frequency comb (BFC) provides a powerful platform for high-dimensional quantum information processing in its spectral and temporal quantum modes. Here we propose and generate a singly-filtered high-dimensional BFC via spontaneous parametric down-conversion by spectrally shaping only the signal photons with a Fabry-Pérot cavity. High-dimensional energy-time entanglement is verified through Franson-interference recurrences and temporal correlation with low-jitter detectors. Frequency- and temporal- entanglement of our singly-filtered BFC is then quantified by Schmidt mode decomposition. Subsequently, we distribute the high-dimensional singly-filtered BFC state over a 10 km fiber link with a post-distribution time-bin dimension lower bounded to be at least 168. Our demonstrations of high-dimensional entanglement and entanglement distribution show the singly-filtered quantum frequency comb’s capability for high-efficiency quantum information processing and high-capacity quantum networks.
The Stochastic Climate Model helps reveal the role of memory in internal variability in the Bohai and Yellow Sea
Authors: Lin Lin , von Storch Hans , Chen Xueen 
Published: October 2023

AbstractHasselmann’s theory elucidates how short-term random noise leads to longer-term unprovoked variations, i.e., red spectra. Here, we study ensembles of numerical model simulations of the hydrodynamics of the Bohai and Yellow Sea concerning internal variability formation. Short(/long) term variations are associated with small(/large) spatial scales, and the internal variability of long-term temporal and large-scale variations is markedly enhanced, even without external forcing on these scales, when the tides are turned off. This pattern is well explained by Hasselmann’s theory. A critical element in this theory is the concept of memory, which in our ensembles exhibits a scale dependence that aligns with the scale-dependent nature of redness. Additionally, this framework clarifies why there is a significant reduction of long-term fluctuations during winter and when tides are active: the system’s memory is notably diminished under these conditions.
In planta expression of human polyQ-expanded huntingtin fragment reveals mechanisms to prevent disease-related protein aggregation
Authors: Llamas Ernesto , Koyuncu Seda , Lee Hyun Ju , Wehrmann Markus , Gutierrez-Garcia Ricardo , Dunken Nick , Charura Nyasha , Torres-Montilla Salvador , Schlimgen Elena , Mandel Amrei M. , Theile Erik Boelen , Grossbach Jan , Wagle Prerana , Lackmann Jan-Wilm , Schermer Bernhard , Benzing Thomas , Beyer Andreas , Pulido Pablo , Rodriguez-Concepcion Manuel , Zuccaro Alga , Vilchez David 
Published: October 2023

AbstractIn humans, aggregation of polyglutamine repeat (polyQ) proteins causes disorders such as Huntington’s disease. Although plants express hundreds of polyQ-containing proteins, no pathologies arising from polyQ aggregation have been reported. To investigate this phenomenon, we expressed an aggregation-prone fragment of human huntingtin (HTT) with an expanded polyQ stretch (Q69) in Arabidopsis thaliana plants. In contrast to animal models, we find that Arabidopsis sp. suppresses Q69 aggregation through chloroplast proteostasis. Inhibition of chloroplast proteostasis diminishes the capacity of plants to prevent cytosolic Q69 aggregation. Moreover, endogenous polyQ-containing proteins also aggregate on chloroplast dysfunction. We find that Q69 interacts with the chloroplast stromal processing peptidase (SPP). Synthetic Arabidopsis SPP prevents polyQ-expanded HTT aggregation in human cells. Likewise, ectopic SPP expression in Caenorhabditis elegans reduces neuronal Q67 aggregation and subsequent neurotoxicity. Our findings suggest that synthetic plant proteins, such as SPP, hold therapeutic potential for polyQ disorders and other age-related diseases involving protein aggregation.
Discrimination exposure impacts unhealthy processing of food cues: crosstalk between the brain and gut
Authors: Zhang Xiaobei , Wang Hao , Kilpatrick Lisa A. , Dong Tien S. , Gee Gilbert C. , Labus Jennifer S. , Osadchiy Vadim , Beltran-Sanchez Hiram , Wang May C. , Vaughan Allison , Gupta Arpana 
Published: October 2023

AbstractExperiences of discrimination are associated with adverse health outcomes, including obesity. However, the mechanisms by which discrimination leads to obesity remain unclear. Utilizing multi-omics analyses of neuroimaging and fecal metabolites, we investigated the impact of discrimination exposure on brain reactivity to food images and associated dysregulations in the brain–gut–microbiome system. We show that discrimination is associated with increased food-cue reactivity in frontal-striatal regions involved in reward, motivation and executive control; altered glutamate-pathway metabolites involved in oxidative stress and inflammation as well as preference for unhealthy foods. Associations between discrimination-related brain and gut signatures were skewed towards unhealthy sweet foods after adjusting for age, diet, body mass index, race and socioeconomic status. Discrimination, as a stressor, may contribute to enhanced food-cue reactivity and brain–gut–microbiome disruptions that can promote unhealthy eating behaviors, leading to increased risk for obesity. Treatments that normalize these alterations may benefit individuals who experience discrimination-related stress.
Resistive relativistic MHD simulations of astrophysical jets
Authors: Mattia G. , Del Zanna L. , Bugli M. , Pavan A. , Ciolfi R. , Bodo G. , Mignone A. 
Published: September 2023

Aims. The main goal of the present paper is to provide the first systematic numerical study of the propagation of astrophysical relativistic jets, in the context of high-resolution, shock-capturing Resistive Relativistic MagnetoHydroDynamic (RRMHD) simulations. We aim to investigate different values and models for the plasma resistivity coefficient, and to assess their impact on the level of turbulence, the formation of current sheets and reconnection plasmoids, the electromagnetic energy content, and the dissipated power.
Methods. We used the PLUTO code for simulations and we assumed an axisymmetric setup for the jets, endowed with both poloidal and toroidal magnetic fields, and propagating in a uniform magnetized medium. The gas was assumed to be characterized by a realistic, Synge-like equation of state (the Taub equation), appropriate for such astrophysical jets. The Taub equation was combined here for the first time with the implicit-explicit Runge-Kutta time-stepping procedure, as required in RRMHD simulations.
Results. The main result is that turbulence is clearly suppressed for the highest values of resistivity (low Lundquist numbers), current sheets are broader, and plasmoids are barely present, while for low values of resistivity the results are very similar to ideal runs, in which dissipation is purely numerical. We find that recipes employing a variable resistivity based on the advection of a jet tracer or on the assumption of a uniform Lundquist number improve on the use of a constant coefficient and are probably more realistic possible sites for the acceleration of the nonthermal particles that produce the observed high-energy emission, preserving as they do the development of turbulence and of sharp current sheets.
Adhesion of 111Indium-Labeled Platelets to the Defoamers of Two Types of Bentley BOS-10 Oxygenators
Authors: Hope A. F. , Heyns A. du P. , Lötter M.G. , Meyer J. M. 
Published: October 2023

111Indium-labelled autologus blood platelets administered to patients preoperatively can be traced in the components of the extracorporeal circuit by gamma camera scintillation imaging. Quantitative assessments can be made of platelet/biomaterial adhesion.
It was thus possible to compare the ratio of adherent platelets on the defoaming systems of two types of Bentley BOS-10 oxygenators. The results indicated that more platelets adhered to the areas of the defoamer where gas bubbles burst than to areas such as the gaseous micro-emboli inhibitor sponge through which all the bubbles had to pass in the later types of BOS-10 oxygenator. In both types the pattern of platelet adhesion to the defoamer layers was comparable and was not influenced by bypass time. Gamma camera images of the oxygenators showed that most platelet adhesion took place in areas of blood/gas to biomaterial interfaces. Tubing circuits and cannulae displayed negligible 111 Indium activity on their surfaces, while the oxygenators held a mean of 8.5% of the activity administered to the patients. This technique could be applied to study platelet interaction with various extracorporeal circuits and oxygenators and may help to clarify the role of cardiopulmonary bypass (CPB) in thrombocytopoenia during heart surgery cases.
Classification of the HCN isomerization reaction dynamics in Ar buffer gas via machine learning
Authors: Yamashita Takefumi , Miyamura Naoaki , Kawai Shinnosuke 
Published: September 2023

The effect of the presence of Ar on the isomerization reaction HCN ⇄ CNH is investigated via machine learning. After the potential energy surface function is developed based on the CCSD(T)/aug-cc-pVQZ level ab initio calculations, classical trajectory simulations are performed. Subsequently, with the aim of extracting insights into the reaction dynamics, the obtained reactivity, that is, whether the reaction occurs or not under a given initial condition, is learned as a function of the initial positions and momenta of all the atoms in the system. The prediction accuracy of the trained model is greater than 95%, indicating that machine learning captures the features of the phase space that affect reactivity. Machine learning models are shown to successfully reproduce reactivity boundaries without any prior knowledge of classical reaction dynamics theory. Subsequent analyses reveal that the Ar atom affects the reaction by displacing the effective saddle point. When the Ar atom is positioned close to the N atom (resp. the C atom), the saddle point shifts to the CNH (HCN) region, which disfavors the forward (backward) reaction. The results imply that analyses aided by machine learning are promising tools for enhancing the understanding of reaction dynamics.
Reduced-order autodifferentiable ensemble Kalman filters
Authors: Chen Yuming , Sanz-Alonso Daniel , Willett Rebecca 
Published: October 2023

Abstract
This paper introduces a computational framework to reconstruct and forecast a partially observed state that evolves according to an unknown or expensive-to-simulate dynamical system. Our reduced-order autodifferentiable ensemble Kalman filters (ROAD-EnKFs) learn a latent low-dimensional surrogate model for the dynamics and a decoder that maps from the latent space to the state space. The learned dynamics and decoder are then used within an EnKF to reconstruct and forecast the state. Numerical experiments show that if the state dynamics exhibit a hidden low-dimensional structure, ROAD-EnKFs achieve higher accuracy at lower computational cost compared to existing methods. If such structure is not expressed in the latent state dynamics, ROAD-EnKFs achieve similar accuracy at lower cost, making them a promising approach for surrogate state reconstruction and forecasting.
Hadron transverse momentum distributions in the Tsallis statistics with escort probabilities
Authors: Parvan A S 
Published: September 2023

Abstract
The exact and approximate hadron transverse momentum distributions for the Fermi–Dirac, Bose–Einstein and Maxwell-Boltzmann statistics of particles in the framework of the Tsallis statistics with escort probabilities (the Tsallis-3 statistics) have been derived. The classical and quantum transverse momentum distributions in the zeroth term approximation and the quantum transverse momentum distributions in the factorization approximation introduced in the zeroth term approximation were found. The transverse momentum distributions in the zeroth term approximation and in the factorization approximation of the zeroth term approximation are the same in the Tsallis-3, Tsallis-2 and q-dual statistics. The well-known classical phenomenological Tsallis distribution exactly coincides with the classical transverse momentum distribution of the Tsallis-3 statistics in the zeroth term approximation for which the entropy of the system is zero in the whole range of state variables. However, the quantum phenomenological Tsallis distribution does not coincide with either the exact or approximate transverse momentum distributions of the Tsallis-3 statistics. The exact Tsallis-3 classical distribution and the classical phenomenological Tsallis distribution were applied to describe the experimental spectra of the charged pions produced in the proton-proton collisions at high energies. The values of the parameters (T, q) for both these model distributions differ in the whole energy range. Thus, the classical phenomenological Tsallis distribution is an unsatisfactory approximation for the exact classical transverse momentum distribution of the Tsallis-3 statistics.
Generalizing the Gurson model using symbolic regression and transfer learning to relax inherent assumptions
Authors: Birky Donovan , Garbrecht Karl , Emery John , Alleman Coleman , Bomarito Geoffrey , Hochhalter Jacob 
Published: September 2023

Abstract
To generate material models with fewer limiting assumptions while maintaining closed-form, interpretable solutions, we propose using genetic programming based symbolic regression (GPSR), a machine learning (ML) approach that describes data using free-form symbolic expressions. To maximize interpretability, we start from an analytical, derived material model, the Gurson model for porous ductile metals, and systematically relax inherent assumptions made in its derivation to understand each assumption’s contribution to the GPSR model forms. We incorporate transfer learning methods into the GPSR training process to increase GPSR efficiency and generate models that abide by known mechanics of the system. The results show that regularizing the GPSR fitness function is critical for generating physically valid models and illustrate how GPSR allows a high level of interpretability compared with other ML approaches. The method of systematic assumption relaxation allows the generation of models that address limiting assumptions found in the Gurson model, and the symbolic forms allow conjecture of decreased material strength due to void interaction and non-symmetric void shapes.