bluuebunny/crossref_metadata_2025_split huggingface dataset:
The synergetic effect of sitafloxacin–arbekacin combination in the Mycobacterium abscessus species
Authors: Watanabe Junko , Ihara Hiroaki , Takei Satomi , Nakamura Ayako , Fujimoto Yuichi , Handoh Tetsuya , Kurokawa Kana , Arai Yuta , Shibayama Kohei , Sumiyoshi Issei , Ochi Yusuke , Okabe Takahiro , Misawa Shigeki , Togo Shinsaku , Naito Toshio , Tabe Yoko , Miida Takashi , Takahashi Kazuhisa 
Published: February 2023

AbstractMycobacterium abscessus species (MABS) is the most commonly isolated rapidly growing mycobacteria (RGM) and is one of the most antibiotic-resistant RGM with rapid progression, therefore, treatment of MABS is still challenging. We here presented a new combination treatment with sitafloxacin that targeted rough morphotypes of MABS, causing aggressive infections. Thirty-four clinical strains of MABS were isolated from various clinical samples at the Juntendo university hospital from 2011 to 2020. The susceptibility to a combination of sitafloxacin and antimicrobial agents was compared to that of the antimicrobial agents alone. Out of 34 MABS, 8 strains treated with sitafloxacin–amikacin combination, 9 of sitafloxacin–imipenem combination, 19 of sitafloxacin–arbekacin combination, and 9 of sitafloxacin–clarithromycin combination showed synergistic effects, respectively. Sitafloxacin–arbekacin combination also exhibited the synergistic effects against 10 of 22 Mycobacterium abscessus subspecies massiliense (Mma) strains and 8 of 11 Mycobacterium abscessus subspecies abscessus (Mab) strains, a highly resistant subspecies of MABS. The sitafloxacin–arbekacin combination revealed more synergistic effects in rough morphotypes of MABS (p = 0.008). We demonstrated the synergistic effect of the sitafloxacin–arbekacin combination against MABS. Further, this combination regimen might be more effective against Mab or rough morphotypes of MABS.
Combining thermal, tri-stereo optical and bi-static InSAR satellite imagery for lava volume estimates: the 2021 Cumbre Vieja eruption, La Palma
Authors: Plank Simon , Shevchenko Alina V. , d’Angelo Pablo , Gstaiger Veronika , González Pablo J. , Cesca Simone , Martinis Sandro , Walter Thomas R. 
Published: February 2023

AbstractDetermining outline, volume and effusion rate during an effusive volcanic eruption is crucial as it is a major controlling factor of the lava flow lengths, the prospective duration and hence the associated hazards. We present for the first time a multi-sensor thermal-and-topographic satellite data analysis for estimating lava effusion rates and volume. At the 2021 lava field of Cumbre Vieja, La Palma, we combine VIIRS + MODIS thermal data-based effusion rate estimates with DSMs analysis derived from optical tri-stereo Pléiades and TanDEM-X bi-static SAR-data. This multi-sensor-approach allows to overcome limitations of single-methodology-studies and to achieve both, high-frequent observation of the relative short-term effusion rate trends and precise total volume estimates. We find a final subaerial-lava volume of $$212\times {10}^{6}\pm 13\times {10}^{6}\; \text{m}^{3}$$

212
×

10

6

±
13
×

10

6

m
3

with a MOR of 28.8 ± 1.4 m3/s. We identify an initially sharp eruption-rate-peak, followed by a gradually decreasing trend, interrupted by two short-lived-peaks in mid/end November. High eruption rate accompanied by weak seismicity was observed during the early stages of the eruption, while during later stage the lava effusion trend coincides with seismicity. This article demonstrates the geophysical monitoring of eruption rate fluctuations, that allows to speculate about changes of an underlying pathway during the 2021 Cumbre Vieja eruption.
Mechanical performance and thermal stability of hardened Portland cement-recycled sludge pastes containing MnFe2O4 nanoparticles
Authors: Mohamed O. A. , El-dek S. I. , El-Gamal S. M. A. 
Published: February 2023

AbstractThis study focused on investigating the possibility of using different ratios (5, 10, 15 mass%) of recycled alum sludge (RAS) as partial replacement of ordinary Portland cement (OPC), to contribute to solving the problems encountered by cement production as well as stockpiling of large quantities of water-treated sludge waste. MnFe2O4 spinel nanoparticles (NMFs) were used to elaborate the mechanical characteristics and durability of different OPC-RAS blends. The outcomes of compressive strength, bulk density, water absorption, and stability against firing tests fastened the suitability of utilization of RAS waste for replacing OPC (maximum limit 10%). The inclusion of different doses of NMFs nanoparticles (0.5, 1 and 2 mass %) within OPC–RAS pastes, motivates the configuration of hardened nanocomposites with improved physico-mechanical characteristics and stability against firing. Composite made from 90% OPC–10% RAS–0.5% NMFs presented the best characteristics and consider the optimal choice for general construction applications. Thermogravimetric analysis (TGA/DTG), X-ray diffraction analysis (XRD), and scanning electron microscope (SEM) techniques. affirmed the positive impact of NMFs particles, as they demonstrated the formation of enormous phases as ilvaite (CFSH), calcium silicate hydrates (CSHs), MnCSH, Nchwaningite [Mn2 SiO3(OH)2 H2O], [(Mn, Ca) Mn4O9⋅3H2O], calcium aluminosilicate hydrates (CASH), Glaucochroite [(Ca, Mn)2SiO4, and calcium ferrite hydrate (CFH). These hydrates boosted the robustness and degradation resistance of the hardened nanocomposites upon firing.
Understanding microbiome dynamics via interpretable graph representation learning
Authors: Melnyk Kateryna , Weimann Kuba , Conrad Tim O. F. 
Published: February 2023

AbstractLarge-scale perturbations in the microbiome constitution are strongly correlated, whether as a driver or a consequence, with the health and functioning of human physiology. However, understanding the difference in the microbiome profiles of healthy and ill individuals can be complicated due to the large number of complex interactions among microbes. We propose to model these interactions as a time-evolving graph where nodes represent microbes and edges are interactions among them. Motivated by the need to analyse such complex interactions, we develop a method that can learn a low-dimensional representation of the time-evolving graph while maintaining the dynamics occurring in the high-dimensional space. Through our experiments, we show that we can extract graph features such as clusters of nodes or edges that have the highest impact on the model to learn the low-dimensional representation. This information is crucial for identifying microbes and interactions among them that are strongly correlated with clinical diseases. We conduct our experiments on both synthetic and real-world microbiome datasets.
Energy management system in smart buildings based coalition game theory with fog platform and smart meter infrastructure
Authors: Saeed Mohammed A. , Eladl Abdelfattah A. , Alhasnawi Bilal Naji , Motahhir Saad , Nayyar Anand , Shah Mohd Asif , Sedhom Bishoy E. 
Published: February 2023

AbstractThis paper proposes a central energy management system (EMS) in smart buildings. It is based on the coalition method for optimal energy sharing between smart buildings. Game theory is applied to obtain an optimal allocation of the building's surplus energy on the deficient energy buildings using the Shapley value, which enables the unequal energy distribution based on the energy demand. The main objective is reducing energy waste while preserving the generation/demand balance. The fog platform with memory storage is applied, which handles all the measured data from the smart buildings through Wi-Fi-based communication protocol and performs the EMS program. The smart meter links the smart buildings with the fog-based EMS central unit. Two scenarios are implemented based on the difference between total deficient and surplus energy. Coalition game theory is applied for optimal surplus energy allocation on deficient buildings when the total energy surplus is lower than the total energy deficient. Also, there is a one-to-one relationship between the surplus and deficient building; if the surplus energy is larger than the deficit, the extra surplus energy is stored for further usage. The proposed EMS is applied and tested using a smart city with 10 buildings in the MATLAB program. A comparison between the result obtained with and without applying the proposed method is performed. The performance of the fog platform is introduced based on the run and delay time and the memory size usage. The results show the effectiveness of the proposed EMS in a smart building.
Comparing bound entanglement of bell diagonal pairs of qutrits and ququarts
Authors: Popp Christopher , Hiesmayr Beatrix C. 
Published: February 2023

AbstractWe compare the classification as entangled or separable of Bell diagonal bipartite qudits with positive partial transposition (PPT) and their properties for different dimensions. For dimension $$d \ge 3$$

d
≥
3

, a form of entanglement exists that is hard to detect and called bound entanglement due to the fact that such entangled states cannot be used for entanglement distillation. Up to this date, no efficient solution is known to differentiate bound entangled from separable states. We address and compare this problem named separability problem for a family of bipartite Bell diagonal qudits with special algebraic and geometric structures and applications in quantum information processing tasks in different dimensions. Extending analytical and numerical methods and results for Bell diagonal qutrits ($$d=3$$

d
=
3

), we successfully classify more than $$75\%$$

75
%

of representative Bell diagonal PPT states for $$d=4$$

d
=
4

. Via those representative states we are able to estimate the volumes of separable and bound entangled states among PPT ququarts ($$d=4$$

d
=
4

). We find that at least $$75.7\%$$

75.7
%

of all PPT states are separable, $$1.7\%$$

1.7
%

bound entangled and for $$22.6\%$$

22.6
%

it remains unclear whether they are separable or bound entangled. Comparing the structure of bound entangled states and their detectors, we find considerable differences in the detection capabilities for different dimensions and relate those to differences of the Euclidean geometry for qutrits ($$d=3$$

d
=
3

) and ququarts ($$d=4$$

d
=
4

). Finally, using a detailed visual analysis of the set of separable and bound entangled Bell diagonal states in both dimensions, qualitative observations are made that allow to better distinguish bound entangled from separable states.
Establishing a simple perfusion cell culture system for light-activated liposomes
Authors: Ilvesroiha Eija , Lauren Patrick , Uema Natsumi , Kikuchi Kanako , Takashima Yuuki , Laaksonen Timo , Lajunen Tatu 
Published: February 2023

AbstractThe off-target effects of light-activated or targeted liposomes are difficult to distinguish in traditional well plate experiments. Additionally, the absence of fluid flow in traditional cell models can lead to overestimation of nanoparticle uptake. In this paper, we established a perfusion cell culture platform to study light-activated liposomes and determined the effect of flow on the liposomal cell uptake. The optimal cell culturing parameters for the A549 cells under flow conditions were determined by monitoring cell viability. To determine optimal liposome treatment times, particle uptake was measured with flow cytometry. The suitability of commercial QuasiVivo flow-chambers for near-infrared light activation was assessed with a calcein release study. The chamber material did not hinder the light activation and subsequent calcein release from the liposomes. Furthermore, our results show that the standard cell culturing techniques are not directly translatable to flow cultures. For non-coated liposomes, the uptake was hindered by flow. Interestingly, hyaluronic acid coating diminished the uptake differences between the flow and static conditions. The study demonstrates that flow affects the liposomal uptake by lung cancer cell line A549. The flow also complicates the cell attachment of A549 cells. Moreover, we show that the QuasiVivo platform is suitable for light-activation studies.
Rigidity control mechanism by turgor pressure in plants
Authors: Kanahama Tohya , Tsugawa Satoru , Sato Motohiro 
Published: February 2023

AbstractThe bodies of herbaceous plants are slender, thin, and soft. These plants support their bodies through the action of turgor pressure associated with their internal water stores. The purpose of this study was to apply the principles of structural mechanics to clarify the underlying mechanism of rigidity control that is responsible for turgor pressure in plants and the reason behind the self-supporting ability of herbaceous plants. We modeled a plant a horizontally oriented thin-walled cylindrical cantilever with closed ends enclosing a cavity filled with water that is acted on by its own weight and by internal tension generated through turgor pressure. We derived an equation describing the plant’s consequent deflection, introducing a dimensionless parameter to express the decrease in deflection associated with the action of turgor pressure. We found that the mechanical and physical characteristics of herbaceous plants that would appear to be counter-productive from a superficial perspective increase the deflection decreasing effect of turgor pressure.
PRR11 is a prognostic biomarker and correlates with immune infiltrates in bladder urothelial carcinoma
Authors: Ni Wenpeng , Yi Lijuan , Dong Xiaoru , Cao Mengjie , Zheng Jinjuan , Wei Qingling , Yuan Chunlei 
Published: February 2023

AbstractAbnormal proline-rich protein 11 (PRR11) expression is associated with various tumors. However, there are few reports concerning PRR11 with prognostic risk, immune infiltration, or immunotherapy of bladder urothelial carcinoma (BLCA). This study is based on online databases, such as Oncomine, GEPIA, HPA, LinkedOmics, TIMER, ESTIMATE and TISIDB, and BLCA data downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus, we employed an array of bioinformatics methods to explore the potential oncogenic roles of PRR11, including analyzing the relationship between PRR11 and prognosis, tumor mutational burden (TMB), microsatellite instability, and immune cell infiltration in BLCA. The results depict that PRR11 is highly expressed in BLCA, and BLCA patients with higher PRR11 expression have worse outcomes. In addition, there was a significant correlation between PRR11 expression and TMB and tumor immune infiltration. These findings suggest that PRR11 can be used as a potential marker for BLCA patient assessment and risk stratification to improve clinical prognosis, and its potential regulatory mechanism in the BLCA tumor microenvironment and targeted therapy is worthy of further investigation.
SH2D4A promotes centrosome maturation to support spindle microtubule formation and mitotic progression
Authors: Yuki Ryuzaburo , Ikeda Yuki , Yasutake Ryuji , Saito Youhei , Nakayama Yuji 
Published: February 2023

AbstractMitotic progression requires the precise formation of spindle microtubules based on mature centrosomes. During the G2/M transition, centrosome maturation progresses, and associated microtubules bundle to form mitotic spindle fibers and capture the chromosomes for alignment at the cell equator. Mitotic kinases-induced phosphorylation signaling is necessary for these processes. Here, we identified SH2 domain-containing protein 4A (SH2D4A/PPP1R38) as a new mitotic regulator. SH2D4A knockdown delays mitotic progression. The time-lapse imaging analysis showed that SH2D4A specifically contributes to the alignment of chromosomes. The cold treatment assay and microtubule regrowth assay indicated that SH2D4A promotes microtubule nucleation to support kinetochore–microtubule attachment. This may be due to the centrosome maturation by SH2D4A via centrosomal recruitment of pericentriolar material (PCM) such as cep192, γ-tubulin, and PLK1. SH2D4A was found to be a negative regulator of PP1 phosphatase. Consistently, treatment with a PP1 inhibitor rescues SH2D4A-knockdown-induced phenotypes, including the microtubule nucleation and centrosomal recruitment of active PLK1. These results suggest that SH2D4A is involved in PCM recruitment to centrosomes and centrosome maturation through attenuation of PP1 phosphatases, accelerating the spindle formation and supporting mitotic progression.
Durable responses to alectinib in murine models of EML4-ALK lung cancer requires adaptive immunity
Authors: Kleczko Emily K. , Hinz Trista K. , Nguyen Teresa T. , Gurule Natalia J. , Navarro Andre , Le Anh T. , Johnson Amber M. , Kwak Jeff , Polhac Diana I. , Clambey Eric T. , Weiser-Evans Mary , Merrick Daniel T. , Yang Michael C. , Patil Tejas , Schenk Erin L. , Heasley Lynn E. , Nemenoff Raphael A. 
Published: February 2023

AbstractLung cancers bearing oncogenic EML4-ALK fusions respond to targeted tyrosine kinase inhibitors (TKIs; e.g., alectinib), with variation in the degree of shrinkage and duration of treatment (DOT). However, factors that control this response are not well understood. While the contribution of the immune system in mediating the response to immunotherapy has been extensively investigated, less is known regarding the contribution of immunity to TKI therapeutic responses. We previously demonstrated a positive association of a TKI-induced interferon gamma (IFNγ) transcriptional response with DOT in EGFR-mutant lung cancers. Herein, we used three murine models of EML4-ALK lung cancer to test the role for host immunity in the alectinib therapeutic response. The cell lines (EA1, EA2, EA3) were propagated orthotopically in the lungs of immunocompetent and immunodeficient mice and treated with alectinib. Tumor volumes were serially measured by μCT and immune cell content was measured by flow cytometry and multispectral immunofluorescence. Transcriptional responses to alectinib were assessed by RNAseq and secreted chemokines were measured by ELISA. All cell lines were similarly sensitive to alectinib in vitro and as orthotopic tumors in immunocompetent mice, exhibited durable shrinkage. However, in immunodeficient mice, all tumor models rapidly progressed on TKI therapy. In immunocompetent mice, EA2 tumors exhibited a complete response, whereas EA1 and EA3 tumors retained residual disease that rapidly progressed upon termination of TKI treatment. Prior to treatment, EA2 tumors had greater numbers of CD8+ T cells and fewer neutrophils compared to EA1 tumors. Also, RNAseq of cancer cells recovered from untreated tumors revealed elevated levels of CXCL9 and 10 in EA2 tumors, and higher levels of CXCL1 and 2 in EA1 tumors. Analysis of pre-treatment patient biopsies from ALK+ tumors revealed an association of neutrophil content with shorter time to progression. Combined, these data support a role for adaptive immunity in durability of TKI responses and demonstrate that the immune cell composition of the tumor microenvironment is predictive of response to alectinib therapy.
Observation of distinct phase transitions in a nonlinear optical Ising machine
Authors: Kumar Santosh , Li Zhaotong , Bu Ting , Qu Chunlei , Huang Yuping 
Published: February 2023

AbstractOptical Ising machines promise to solve complex optimization problems with an optical hardware acceleration advantage. Here we study the ground state properties of a nonlinear optical Ising machine realized by spatial light modulator, Fourier optics, and second-harmonic generation in a nonlinear crystal. By tuning the ratio of the light intensities at the fundamental and second-harmonic frequencies, we experimentally observe two distinct ferromagnetic-to-paramagnetic phase transitions: a second-order phase transition where the magnetization changes to zero continuously and a first-order phase transition where the magnetization drops to zero abruptly as the effective temperature increases. Our experimental results are corroborated by a numerical simulation based on the Monte Carlo Metropolis-Hastings algorithm, and the physical mechanism for the distinct phase transitions can be understood with a mean-field theory. Our results showcase the flexibility of the nonlinear optical Ising machine, which may find potential applications in solving combinatorial optimization problems.
Multi‐state unified calculation model of rail potential and stray current in DC railway systems
Authors: Du Guifu , Zheng Zixuan , Li Qiaoyue , Xu Fengchuan , Zhang Tianye , Zhang Dongliang , Zhang Xiaoping , Huang Weiguo 
Published: February 2023

AbstractIn order to calculate the dynamic distribution of rail potential and stray current accurately, a multi‐state unified calculation model of rail potential and stray current is proposed, and the characteristics of different protection devices and reflux system in multi‐state DC railway systems are analysed. In the proposed model, the multi‐state characteristics of the traction substation, train, protection devices and reflux system are uniformly simulated by unified node models. The mixed simulation parameters of the catenary and reflux system are unified to lumped parameter networks, and the multi‐node voltage equations are established based on the simulation model. Then, the power flow of DC railway systems is calculated using an iterative solution, and the dynamic distribution of rail potential and stray current are solved by differential equations. The multi‐state unified calculation model is built and the distribution of rail potential and stray current in different conditions are simulated based on the parameters of Wuxi Subway Line 2. In order to verify the multi‐state unified calculation model proposed, field tests and simulations are carried out. Results show that the multi‐state unified calculation model can unify the complex states of DC railway systems and calculate the distribution of rail potential and stray current accurately.
Industrial anomaly detection with multiscale autoencoder and deep feature extractor‐based neural network
Authors: Tang Ta‐Wei , Hsu Hakiem , Li Kuan‐Ming 
Published: February 2023

AbstractWith the maturity of deep learning image recognition technology and the popularity of automated production lines, deep learning industrial anomaly detection has become an important research topic in recent years. In this study, an anomaly detection model with a multi‐scale autoencoder and deep feature extractor is proposed. This model was confirmed to obtain the highest area under the curve (AUC) in 14 of the 17 industrial detection tasks. In addition, the receiver operating characteristic (ROC) curves show that an appropriate threshold of the proposed model exists, which can achieve a low false‐positive rate and maintain a high true‐positive rate. Furthermore, the influence of different feature extractors on the method is discussed. It was shown that the proposed method can maintain good detection ability with most of the feature extractor. Therefore, it is suitable for industrial optical inspection systems with different hardware conditions.