bluuebunny/crossref_metadata_2025_split huggingface dataset:
RNaseH2A downregulation drives inflammatory gene expression via genomic DNA fragmentation in senescent and cancer cells
Authors: Sugawara Sho , Okada Ryo , Loo Tze Mun , Tanaka Hisamichi , Miyata Kenichi , Chiba Masatomo , Kawasaki Hiroko , Katoh Kaoru , Kaji Shizuo , Maezawa Yoshiro , Yokote Koutaro , Nakayama Mizuho , Oshima Masanobu , Nagao Koji , Obuse Chikashi , Nagayama Satoshi , Takubo Keiyo , Nakanishi Akira , Kanemaki Masato T. , Hara Eiji , Takahashi Akiko 
Published: December 2022

AbstractCellular senescence caused by oncogenic stimuli is associated with the development of various age-related pathologies through the senescence-associated secretory phenotype (SASP). SASP is mediated by the activation of cytoplasmic nucleic acid sensors. However, the molecular mechanism underlying the accumulation of nucleotide ligands in senescent cells is unclear. In this study, we revealed that the expression of RNaseH2A, which removes ribonucleoside monophosphates (rNMPs) from the genome, is regulated by E2F transcription factors, and it decreases during cellular senescence. Residual rNMPs cause genomic DNA fragmentation and aberrant activation of cytoplasmic nucleic acid sensors, thereby provoking subsequent SASP factor gene expression in senescent cells. In addition, RNaseH2A expression was significantly decreased in aged mouse tissues and cells from individuals with Werner syndrome. Furthermore, RNaseH2A degradation using the auxin-inducible degron system induced the accumulation of nucleotide ligands and induction of certain tumourigenic SASP-like factors, promoting the metastatic properties of colorectal cancer cells. Our results indicate that RNaseH2A downregulation provokes SASP through nucleotide ligand accumulation, which likely contributes to the pathological features of senescent, progeroid, and cancer cells.
Geodesy of irregular small bodies via neural density fields
Authors: Izzo Dario , Gómez Pablo 
Published: December 2022

AbstractAsteroids’ and comets’ geodesy is a challenging yet important task for planetary science and spacecraft operations, such as ESA’s Hera mission tasked to look at the aftermath of the recent NASA DART spacecraft’s impact on Dimorphos. Here we present a machine learning approach based on so-called geodesyNets which learns accurate density models of irregular bodies using minimal prior information. geodesyNets are a three-dimensional, differentiable function representing the density of a target irregular body. We investigate six different bodies, including the asteroids Bennu, Eros, and Itokawa and the comet Churyumov-Gerasimenko, and validate on heterogeneous and homogeneous ground-truth density distributions. Induced gravitational accelerations and inferred body shape are accurate, resulting in a relative acceleration error of less than 1%, also close to the surface. With a shape model, geodesyNets can even learn heterogeneous density fields and thus provide insight into the body’s internal structure. This adds a powerful tool to consolidated approaches like spherical harmonics, mascon models, and polyhedral gravity.
Recent trends towards privacy‐preservation in Internet of Things, its challenges and future directions
Authors: Safaei Yaraziz Mahdi , Jalili Ahmad , Gheisari Mehdi , Liu Yang 
Published: December 2022

AbstractThe Internet of Things (IoT) is a self‐configuring, intelligent system in which autonomous things connect to the Internet and communicate with each other. As ‘things’ are autonomous, it may raise privacy concerns. In this study, the authors describe the background of IoT systems and privacy and security measures, including (a) approaches to preserving privacy in IoT‐based systems, (b) existing privacy solutions, and (c) recommending privacy models for different layers of IoT applications. Based on the results of our study, it is clear that new methods such as Blockchain, Machine Learning, Data Minimisation, and Data Encryption can greatly impact privacy issues to ensure security and privacy. Moreover, it makes sense that users can protect their personal information easier if there is fewer data to collect, store, and share by smart devices. Thus, this study proposes a machine learning‐based data minimisation method that, in these networks, can be very beneficial for privacy‐preserving.
Satisfacción personal y percepción de éxito en mujeres en Traumatología: Factores determinantes en la elección de la especialidad y desarrollo profesional
Authors: Ramírez Constanza , Iñiguez Magaly , Reginato Rafaella , Ibáñez Angélica , Ahumada Ximena 
Published: December 2022

ResumenHistóricamente, las médicas han sido asociadas a especialidades determinadas. En los últimos años, estos estereotipos han sido lentamente revertidos con mayor participación de la mujer en especialidades quirúrgicas. En el proceso de aprendizaje se sabe la importancia que tienen los modelos y mentores. Buscamos evaluar el grado de satisfacción y el éxito profesional de las mujeres en Traumatología, y qué factores cumplieron un rol positivo en la decisión de optar por ella.Se encuestó a 108 mujeres dedicadas a la Traumatología, y se evaluaron las influencias positivas y los mentores como modelo en la toma de decisión por la especialidad y los grados de satisfacción personal y profesional.Pese a una mayor percepción de dificultades en lograr el objetivo, destacan los altos grados de satisfacción profesional y personal de las mujeres en Traumatología: 95% refirió haber elegido la especialidad correcta, 100% afirmó que las dificultades se compensan con los resultados obtenidos, y 96% volvería a elegir la misma especialidad. En relación con la percepción de éxito, 73% se considera exitosa en su vida profesional, y en la vida personal, 85%.Muy relevante en la toma de decisión por la especialidad es el rol que cumplen docentes, mentores, y el gusto por la cirugía y los deportes. Un 84% recibió alguna influencia positiva, 61% tuvo como modelo en su formación una traumatóloga, y un 98% recomendaría a otras mujeres en período de formación que se dedicaran a la Traumatología.Las estrategias de incremento de la participación femenina en la especialidad pudiesen orientarse a fomentar modelos femeninos durante el aprendizaje.
Lesión de Bony Bankart: Conceptos fundamentales para su comprensión y tratamiento
Authors: Morán Nicolás 
Published: December 2022

ResumenLas lesiones óseas en el borde anterior del anillo glenoideo secundarias a un episodio de inestabilidad anterior del hombro cada vez son más reportadas. Conocidas como lesión de Bony Bankart, su presencia genera una pérdida de la estabilidad estática glenohumeral que provoca un aumento del riesgo de un nuevo evento de luxación. Por ende, resulta fundamental que los cirujanos ortopédicos comprendan y diagnostiquen estas lesiones de forma correcta y oportuna para evaluar la necesidad de restaurar la superficie articular glenoidea. El objetivo de esta revisión narrativa es otorgar los conceptos más importantes de la lesión ósea de Bankart para comprender y enfrentar de forma adecuada esta lesión.
Nivel de Evidencia V
Comparison of Trauma in Dogs due to Direct Motor Vehicle Collision or Fall from Open Pick-up Truck Bed during Transportation (2002-2020)
Authors: Salmelin Bettina R.M. , Ueda Yu , Gilbert Peter J. , Martinez Steven A. 
Published: December 2022

Abstract
Objective The aim of this study was to report injuries sustained by dogs following motor vehicle trauma: direct motor vehicle collision (MVC), and fall from an open pickup truck bed during transportation (PTB).
Study Design Medical records of dogs involved in motor vehicle trauma between 2002 and 2020 were reviewed. Signalment, mode of injury, injuries sustained, and treatments performed were recorded. An owner questionnaire investigated effects of the trauma on the dog and owner.
Results Six hundred and ninety-eight dogs met the inclusion criteria (569 MVC, 102 PTB). Orthopaedic trauma was significantly more common after PTB (90.2%) (MVC, 75.6%; p = 0.011). There were not any differences in the prevalence of soft tissue injuries between groups (76.4% MVC, 67.6% PTB; p = 0.058), however, MVC dogs had significantly more thoracic (26.9% MVC, 4.4% PTB) and abdominal (12.9% MVC, 0% PTB) trauma (p <0.001). Surgical treatments were performed significantly more often after PTB (71.6%) (MVC, 47.6%) (p <0.001). Discharge rate after PTB (95.0%) was significantly higher (MVC, 84.0%) (p <0.001). Aftercare was reported to be significantly more difficult after PTB (76.2%) (MVC, 34.0%; p = 0.002).
Conclusion MVC and PTB result in significantly different trauma. PTB causes predominantly orthopaedic and integument injuries, whereas MVC results in thoracic and abdominal trauma. Survival to discharge is greater following PTB than MVC.
Do handgrip strength and dexterity predict respiratory function in neuromuscular disease?
Authors: Safran Ertugrul , Ozer Aysel Yildiz , Gurses Hulya Nilgun 
Published: December 2022

Abstract
Background Neuromuscular diseases are acquired or inherited diseases that affect the function of the muscles in our body, including respiratory muscles.
Objective We aimed to discover more cost-effective and practical tools to predict respiratory function status, which causes serious problems with patients with neuromuscular disease.
Methods The Vignos and Brooke Upper Extremity Functional Scales were used to evaluate functional status for patient recruitment. The handgrip strength and dexterity of patients were measured using a dynamometer and nine-hole peg test. Respiratory function parameters: forced vital capacity, forced expiratory volume in one second, and peak expiratory flow were evaluated using spirometry.
Results The mean age of the 30 patients was 11.5 ± 3.79 years old. Significant relationships were found between nine-hole-peg-test scores and respiratory function parameters on both sides. Significant correlations were found between both handgrip strength and respiratory function parameters (p < 0.05). In the linear regression analysis, it was seen that the forced expiratory volume in 1 second, and peak expiratory flow values could be explained in different percentages (p < 0.05).
Conclusions Handgrip strength and dexterity measurements can be used as indicators for estimating respiratory function parameters in terms of cost and accessibility, although it is known that they will not replace respiratory function tests.
Follistatin regulates the specification of the apical cochlea responsible for low-frequency hearing in mammals
Authors: Koo Hei Yeun , Kim Min-A , Min Hyehyun , Hwang Jae Yeon , Prajapati-DiNubila Meenakshi , Kim Kwan Soo , Matzuk Martin M. , Park Juw Won , Doetzlhofer Angelika , Kim Un-Kyung , Bok Jinwoong 
Published: December 2022

The cochlea’s ability to discriminate sound frequencies is facilitated by a special topography along its longitudinal axis known as tonotopy. Auditory hair cells located at the base of the cochlea respond to high-frequency sounds, whereas hair cells at the apex respond to lower frequencies. Gradual changes in morphological and physiological features along the length of the cochlea determine each region’s frequency selectivity, but it remains unclear how tonotopy is established during cochlear development. Recently, sonic hedgehog (SHH) was proposed to initiate the establishment of tonotopy by conferring regional identity to the primordial cochlea. Here, using mouse genetics, we provide in vivo evidence that regional identity in the embryonic cochlea acts as a framework upon which tonotopy-specific properties essential for frequency selectivity in the mature cochlea develop. We found that follistatin (FST) is required for the maintenance of apical cochlear identity, but dispensable for its initial induction. In a fate-mapping analysis, we found that FST promotes expansion of apical cochlear cells, contributing to the formation of the apical cochlear domain. SHH, in contrast, is required both for the induction and maintenance of apical identity. In the absence of FST or SHH, mice produce a short cochlea lacking its apical domain. This results in the loss of apex-specific anatomical and molecular properties and low-frequency-specific hearing loss.
Bandgap evolution of metamaterials with continuous solid–liquid phase change
Authors: Yuan Wenhan , Chai Yijun , Yang Xiongwei , Li Yueming 
Published: December 2022

Abstract
Owing to the instinct difference in atomic buildings between solid and liquid, the phase change of material can fundamentally change wave energy propagation. In the present work, a novel elastic metamaterial system called solid–liquid phase change metamaterial (SPCM) is proposed, which allows continuous variation of the vibration isolation bandgap in thermal environments. The metamaterial is carefully designed by inserting phase change material (PCM) into an external framework. To reveal how wave propagation is affected by phase change, we develop a theoretical model based on Lagrange’s equation, which can describe the kinematic relations within the metamaterial during the entire phase change process. The model is verified through numerical calculations after the dynamic effective parameters are obtained, and good agreement can be found in the band structure and vibration transmission calculation at different phase change states. Due to the continuous phase change of PCM, the frequency range of the negative effective parameter shifts to lower frequencies, leading to a thermally tunable bandgap. Nevertheless, the constantly changing bandgap covers a certain range during the entire phase change process, indicating that the SPCM designed in this work can offer stable vibration attenuation in a wide range of thermal environments. The design and theory would be critically useful in the design of adaptive metamaterial bandgap in thermal environments.
Simulation-to-real generalization for deep-learning-based refraction-corrected ultrasound tomography image reconstruction
Authors: Zhao Wenzhao , Fan Yuling , Wang Hongjian , Gemmeke Hartmut , van Dongen Koen W A , Hopp Torsten , Hesser Jürgen 
Published: December 2022

Abstract

Objective. The image reconstruction of ultrasound computed tomography is computationally expensive with conventional iterative methods. The fully learned direct deep learning reconstruction is promising to speed up image reconstruction significantly. However, for direct reconstruction from measurement data, due to the lack of real labeled data, the neural network is usually trained on a simulation dataset and shows poor performance on real data because of the simulation-to-real gap. Approach. To improve the simulation-to-real generalization of neural networks, a series of strategies are developed including a Fourier-transform-integrated neural network, measurement-domain data augmentation methods, and a self-supervised-learning-based patch-wise preprocessing neural network. Our strategies are evaluated on both the simulation dataset and real measurement datasets from two different prototype machines. Main results. The experimental results show that our deep learning methods help to improve the neural networks’ robustness against noise and the generalizability to real measurement data. Significance. Our methods prove that it is possible for neural networks to achieve superior performance to traditional iterative reconstruction algorithms in imaging quality and allow for real-time 2D-image reconstruction. This study helps pave the path for the application of deep learning methods to practical ultrasound tomography image reconstruction based on simulation datasets.
Weakly supervised semantic segmentation of histological tissue via attention accumulation and pixel-level contrast learning
Authors: Han Yongqi , Cheng Lianglun , Huang Guoheng , Zhong Guo , Li Jiahua , Yuan Xiaochen , Liu Hongrui , Li Jiao , Zhou Jian , Cai Muyan 
Published: December 2022

Abstract

Objective. Histopathology image segmentation can assist medical professionals in identifying and diagnosing diseased tissue more efficiently. Although fully supervised segmentation models have excellent performance, the annotation cost is extremely expensive. Weakly supervised models are widely used in medical image segmentation due to their low annotation cost. Nevertheless, these weakly supervised models have difficulty in accurately locating the boundaries between different classes of regions in pathological images, resulting in a high rate of false alarms Our objective is to design a weakly supervised segmentation model to resolve the above problems. Approach. The segmentation model is divided into two main stages, the generation of pseudo labels based on class residual attention accumulation network (CRAANet) and the semantic segmentation based on pixel feature space construction network (PFSCNet). CRAANet provides attention scores for each class through the class residual attention module, while the Attention Accumulation (AA) module overlays the attention feature maps generated in each training epoch. PFSCNet employs a network model containing an inflated convolutional residual neural network and a multi-scale feature-aware module as the segmentation backbone, and proposes dense energy loss and pixel clustering modules are based on contrast learning to solve the pseudo-labeling-inaccuracy problem. Main results. We validate our method using the lung adenocarcinoma (LUAD-HistoSeg) dataset and the breast cancer (BCSS) dataset. The results of the experiments show that our proposed method outperforms other state-of-the-art methods on both datasets in several metrics. This suggests that it is capable of performing well in a wide variety of histopathological image segmentation tasks. Significance. We propose a weakly supervised semantic segmentation network that achieves approximate fully supervised segmentation performance even in the case of incomplete labels. The proposed AA and pixel-level contrast learning also make the edges more accurate and can well assist pathologists in their research.
Hierarchies of resources for measurement-based quantum computation
Authors: Frembs Markus , Roberts Sam , Campbell Earl T , Bartlett Stephen D 
Published: December 2022

Abstract
For certain restricted computational tasks, quantum mechanics provides a provable advantage over any possible classical implementation. Several of these results have been proven using the framework of measurement-based quantum computation (MBQC), where nonlocality and more generally contextuality have been identified as necessary resources for certain quantum computations. Here, we consider the computational power of MBQC in more detail by refining its resource requirements, both on the allowed operations and the number of accessible qubits. More precisely, we identify which Boolean functions can be computed in non-adaptive MBQC, with local operations contained within a finite level in the Clifford hierarchy. Moreover, for non-adaptive MBQC restricted to certain subtheories such as stabiliser MBQC, we compute the minimal number of qubits required to compute a given Boolean function. Our results point towards hierarchies of resources that more sharply characterise the power of MBQC beyond the binary of contextuality vs non-contextuality.
The cross-over from Townes solitons to droplets in a 2D Bose mixture
Authors: Bakkali-Hassani B , Maury C , Stringari S , Nascimbene S , Dalibard J , Beugnon J 
Published: December 2022

Abstract
When two Bose–Einstein condensates—labelled 1 and 2—overlap spatially, the equilibrium state of the system depends on the miscibility criterion for the two fluids. Here, we theoretically focus on the non-miscible regime in two spatial dimensions and explore the properties of the localized wave packet formed by the minority component 2 when immersed in an infinite bath formed by component 1. We address the zero-temperature regime and describe the two-fluid system by coupled classical field equations. We show that such a wave packet exists only for an atom number N
2 above a threshold value corresponding to the Townes soliton state. We identify the regimes where this localized state can be described by an effective single-field equation up to the droplet case, where component 2 behaves like an incompressible fluid. We study the near-equilibrium dynamics of the coupled fluids, which reveals specific parameter ranges for the existence of localized excitation modes.
Magnetic properties of two dimensional V
2
O
3 monolayer
Authors: Demir Vatansever Zeynep 
Published: December 2022

Abstract
Two dimensional (2D) magnetic materials with unique properties offer an ideal platform to study magnetic phase transitions in the low-dimensional systems. In this study, we implement extensive Monte Carlo simulations to investigate the magnetic properties of the 2D V
2
O
3 monolayer. By using finite-size scaling tools, we obtain the critical temperature and critical exponents of the monolayer precisely. Our numerical results demonstrate that 2D V
2
O
3 monolayer belongs to the two-dimensional Ising universality class. Besides, we examine the hysteresis characteristics of the structure and show that V
2
O
3 monolayer is a hard ferromagnetic material with a high coercive field at room temperature.
Structure and flexural strength of the hot-pressed AlMgB14 ceramic
Authors: Tkachev Dmitrii , Nikitin Pavel , Zhukov Ilya , Vorozhtsov Alexander , Marchenko Ekaterina , Verkhoshanskiy Yanis , Belchikov Ivan 
Published: December 2022

Abstract
AlMgB14 materials were obtained by hot-pressing of the prereacted AlMgB14 powder. The phase composition, structure, hardness and flexural strength have been studied. The XRD studies shown that the phase composition of the obtained materials contains from 9 to 12 wt. % of the spinel MgAl2O4 phase except target AlMgB14-phase. The spinel content increases linearly with an increase in the hot-pressing temperature from 1400 °C to 1600 °C. It was found that the density of the studied materials non-linearly depends on the hot-pressing temperature. An increase in the hot-pressing temperature from 1400 °C to 1500 °C leads to an increase in the relative density of the samples from 84% to 93%, respectively. A further increase in the hot-pressing temperature to 1600 °C leads to a decrease in the relative density to 81% due to the complication of the densification processes with an increase in the spinel content. An increase in the relative density from 81% to 93% leads to an increase in the flexural strength from 121 to 314 MPa and an increase in the Vickers microhardness from 5.1 to 7.9 GPa, respectively.
Spectroscopy and carrier dynamics of one-dimensional nanostructures
Authors: Zhang Yutong , Zhu Zhuoya , Zhang Shuai , Wu Xianxin , Du Wenna , Liu Xinfeng 
Published: December 2022

Abstract
In recent years, one-dimensional (1D) nanomaterials have raised researcher's interest because of their unique structural characteristic to generate and confine the optical signal and their promising prospects in photonic applications. In this review, we summarized the recent research advances on the spectroscopy and carrier dynamics of 1D nanostructures. First, the condensation and propagation of exciton–polaritons in nanowires (NWs) are introduced. Second, we discussed the properties of 1D photonic crystal (PC) and applications in photonic–plasmonic structures. Third, the observation of topological edge states in 1D topological structures is introduced. Finally, the perspective on the potential opportunities and remaining challenges of 1D nanomaterials is proposed.