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Article: The systemic oxidative stress score has a prognostic value on gastric cancer patients undergoing surgery.

Wang, Xinyu / Zhang, Limin

2024 Volume 14, Page(s) 1307662

Abstract: Background: Oxidative stress is strongly associated with the development, recurrence metastasis, and treatment of gastric cancer. It is yet unknown, though, how systemic oxidative stress levels relate to the surgically treated gastric cancer patients' ... ...

Abstract	Background: Oxidative stress is strongly associated with the development, recurrence metastasis, and treatment of gastric cancer. It is yet unknown, though, how systemic oxidative stress levels relate to the surgically treated gastric cancer patients' clinical results. This research aims to investigate the prognostic effect of systemic oxidative stress score, also known as systematic oxidative stress score (SOS), on gastric cancer patients undergoing surgical treatment. Methods: Development of the SOS Formula through Least Absolute Shrinkage and Selection Operator LASSO Cox Regression. By using optimal cut-off values, the 466 patients included in the study had been split into high SOS and low SOS groups. Utilizing Chi-square test and the Wilcoxon rank sum test, this research examined the relationship between SOS and clinical traits. With the aid of Kaplan-Meier and COX regression analysis, the prognosis of patients with gastric cancer was examined. Results: SOS consisted of four oxidative stress-related laboratory indices. Univariate and multivariate COX regression analyses revealed that SOS, Age, CA724, Radical resection and TNM stage were crucial prognostic factors for OS, and the independent prognostic factors for PFS included Age, CA724, TNM stage and SOS. They could have their prognosis correctly predicted using a nomogram built around SOS and independent prognostic variables. Conclusion: SOS is a practical and reasonably priced tool for determining a patient's prognosis for gastric cancer. More notably, SOS is an accurate prognostic factor for patients with advanced gastric cancer who has undergone radical surgery.
Language	English
Publishing date	2024-03-08
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2649216-7
ISSN	2234-943X
ISSN	2234-943X
DOI	10.3389/fonc.2024.1307662
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Book ; Online: Transfinite Modal Logic

Wang, Xinyu

a Semi-quantitative Explanation for Bayesian Reasoning

2022

Abstract: Bayesian reasoning plays a significant role both in human rationality and in machine learning. In this paper, we introduce transfinite modal logic, which combines modal logic with ordinal arithmetic, in order to formalize Bayesian reasoning semi- ... ...

Abstract	Bayesian reasoning plays a significant role both in human rationality and in machine learning. In this paper, we introduce transfinite modal logic, which combines modal logic with ordinal arithmetic, in order to formalize Bayesian reasoning semi-quantitatively. Technically, we first investigate some nontrivial properties of ordinal arithmetic, which then enable us to expand normal modal logic's semantics naturally and elegantly onto the novel transfinite modal logic, while still keeping the ordinary definition of Kripke models totally intact. Despite all the transfinite mathematical definition, we argue that in practice, this logic can actually fit into a completely finite interpretation as well. We suggest that transfinite modal logic captures the essence of Bayesian reasoning in a rather clear and simple form, in particular, it provides a perfect explanation for Sherlock Holmes' famous saying, "When you have eliminated the impossible, whatever remains, however improbable, must be the truth." We also prove a counterpart of finite model property theorem for our logic.
Keywords	Computer Science - Artificial Intelligence ; Computer Science - Logic in Computer Science ; Mathematics - Logic
Subject code	160
Publishing date	2022-04-02
Publishing country	us
Document type	Book ; Online
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Article ; Online: Deep consistency-preserving hash auto-encoders for neuroimage cross-modal retrieval.

Wang, Xinyu / Zeng, Xianhua

Scientific reports

2023 Volume 13, Issue 1, Page(s) 2316

Abstract: Cross-modal hashing is an efficient method to embed high-dimensional heterogeneous modal feature descriptors into a consistency-preserving Hamming space with low-dimensional. Most existing cross-modal hashing methods have been able to bridge the ... ...

Abstract	Cross-modal hashing is an efficient method to embed high-dimensional heterogeneous modal feature descriptors into a consistency-preserving Hamming space with low-dimensional. Most existing cross-modal hashing methods have been able to bridge the heterogeneous modality gap, but there are still two challenges resulting in limited retrieval accuracy: (1) ignoring the continuous similarity of samples on manifold; (2) lack of discriminability of hash codes with the same semantics. To cope with these problems, we propose a Deep Consistency-Preserving Hash Auto-encoders model, called DCPHA, based on the multi-manifold property of the feature distribution. Specifically, DCPHA consists of a pair of asymmetric auto-encoders and two semantics-preserving attention branches working in the encoding and decoding stages, respectively. When the number of input medical image modalities is greater than 2, the encoder is a multiple pseudo-Siamese network designed to extract specific modality features of different medical image modalities. In addition, we define the continuous similarity of heterogeneous and homogeneous samples on Riemann manifold from the perspective of multiple sub-manifolds, respectively, and the two constraints, i.e., multi-semantic consistency and multi-manifold similarity-preserving, are embedded in the learning of hash codes to obtain high-quality hash codes with consistency-preserving. The extensive experiments show that the proposed DCPHA has the most stable and state-of-the-art performance. We make code and models publicly available: https://github.com/Socrates023/DCPHA .
Language	English
Publishing date	2023-02-09
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-29320-6
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Article ; Online: Prediction of personal default risks based on a sparrow search algorithm with support vector machine model.

Shen, Xu / Wang, Xinyu

Mathematical biosciences and engineering : MBE

2023 Volume 20, Issue 11, Page(s) 19401–19415

Abstract: Aiming at the personal credit evaluation of commercial banks, this paper constructs a classified prediction model based on machine learning methods to predict the default risk. At the same time, this paper proposes to combine the sparrow search algorithm ...

Abstract	Aiming at the personal credit evaluation of commercial banks, this paper constructs a classified prediction model based on machine learning methods to predict the default risk. At the same time, this paper proposes to combine the sparrow search algorithm (SSA) with the support vector machine (SVM) to explore the application of the SSA-SVM model in personal default risk prediction. Therefore, this paper takes the personal credit data as the original data, carries out statistical analysis, normalization and principal factor analysis, and substitutes the obtained variables as independent variables into the SSA-SVM model. Under the premise of the same model, the experimental results show that the evaluation indexes of the experimental data are better than the original data, which shows that it is effective for the data processing operation of the original data in this paper. On the premise of the same data, each evaluation index of the SSA-SVM model is better than the SVM model, which shows that the hybridized model established in this paper is better than the latter one in predicting personal default risk, and has certain practical value.
Language	English
Publishing date	2023-12-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	2265126-3
ISSN	1551-0018 ; 1551-0018
ISSN (online)	1551-0018
ISSN	1551-0018
DOI	10.3934/mbe.2023858
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Article ; Online: Who are the receivers and transmitters of volatility spillovers: oil, clean energy, and green and non-green cryptocurrency markets.

Zhou, En / Wang, Xinyu

Environmental science and pollution research international

2023 Volume 31, Issue 4, Page(s) 5735–5761

Abstract: In the context of clean energy and green cryptocurrency development, the relationship between energy and cryptocurrency markets deserves further exploration. This study employs a quantile time-frequency connectedness approach to measure the dynamic ... ...

Abstract	In the context of clean energy and green cryptocurrency development, the relationship between energy and cryptocurrency markets deserves further exploration. This study employs a quantile time-frequency connectedness approach to measure the dynamic connectedness and volatility propagation mechanisms between oil, clean energy, green cryptocurrency (GC), and non-green cryptocurrency (NGC) markets. Our findings suggest that, at median and low volatility levels, the oil and clean energy markets act as net receivers, taking on volatility spillovers from cryptocurrency markets. However, at high volatility levels, oil and clean energy markets transform into net transmitters. Most NGCs are volatility transmitters, while most GCs are volatility receivers in the median and extremely high volatility cases. We also observe that the total connectedness index (TCI) is heterogeneous over time and dependent on economic events. At median and low volatility levels, the short-run TCI makes the primary contribution. On the other hand, for high volatility levels, where short-term TCI does not have an absolute advantage, long-term TCI plays a greater role in many periods. Additionally, there is asymmetry in the TCI (including long-term and short-term TCI) at the quantile level. In the median and extreme scenarios, the COVID-19 has caused different levels of shock on oil, clean energy, GC, and NGC markets connectedness.
MeSH term(s)	Humans ; COVID-19 ; Reproduction
Language	English
Publishing date	2023-12-22
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1178791-0
ISSN	1614-7499 ; 0944-1344
ISSN (online)	1614-7499
ISSN	0944-1344
DOI	10.1007/s11356-023-29918-3
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Article ; Online: An update on the biological effects of quantum dots: From environmental fate to risk assessment based on multiple biological models.

Wang, Xinyu / Wu, Tianshu

The Science of the total environment

2023 Volume 879, Page(s) 163166

Abstract: Quantum dots (QDs) are zero-dimension nanomaterials with excellent physical and chemical properties, which have been widely used in environmental science and biomedicine. Therefore, QDs are potential to cause toxicity to the environment and enter ... ...

Abstract	Quantum dots (QDs) are zero-dimension nanomaterials with excellent physical and chemical properties, which have been widely used in environmental science and biomedicine. Therefore, QDs are potential to cause toxicity to the environment and enter organisms through migration and bioenrichment effects. This review aims to provide a comprehensive and systematic analysis on the adverse effects of QDs in different organisms based on recently available data. Following PRISMA guidelines, this study searched PubMed database according to the pre-set keywords, and included 206 studies according to the inclusion and elimination criteria. CiteSpace software was firstly used to analyze the keywords of included literatures, search for breaking points of former studies, and summarize the classification, characterization and dosage of QDs. The environment fate of QDs in the ecosystems were then analyzed, followed with comprehensively summarized toxicity outcomes at individual, system, cell, subcellular and molecular levels. After migration and degradation in the environment, aquatic plants, bacteria, fungi as well as invertebrates and vertebrates have been found to be suffered from toxic effects caused by QDs. Aside from systemic effects, toxicity of intrinsic QDs targeting to specific organs, including respiratory system, cardiovascular system, hepatorenal system, nervous system and immune system were confirmed in multiple animal models. Moreover, QDs could be taken up by cells and disturb the organelles, which resulted in cellular inflammation and cell death, including autophagy, apoptosis, necrosis, pyroptosis and ferroptosis. Recently, several innovative technologies, like organoids have been applied in the risk assessment of QDs to promote the surgical interventions of preventing QDs' toxicity. This review not only aimed at updating the research progress on the biological effects of QDs from environmental fate to risk assessment, but also overcame the limitations of available reviews on basic toxicity of nanomaterials by interdisciplinarity and provided new insights for better applications of QDs.
MeSH term(s)	Animals ; Quantum Dots/toxicity ; Quantum Dots/chemistry ; Ecosystem ; Respiratory System ; Apoptosis ; Models, Biological
Language	English
Publishing date	2023-04-01
Publishing country	Netherlands
Document type	Journal Article ; Review
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2023.163166
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Article ; Online: Advances in smart delivery of magnetic field-targeted drugs in cardiovascular diseases.

Wang, Xinyu / Bai, Ruru

Drug delivery

2023 Volume 30, Issue 1, Page(s) 2256495

Abstract: Magnetic Drug Targeting (MDT) is of particular interest to researchers because of its good loading efficiency, targeting accuracy, and versatile use in vivo. Cardiovascular Disease (CVD) is a global chronic disease with a high mortality rate, and the ... ...

Abstract	Magnetic Drug Targeting (MDT) is of particular interest to researchers because of its good loading efficiency, targeting accuracy, and versatile use in vivo. Cardiovascular Disease (CVD) is a global chronic disease with a high mortality rate, and the development of more precise and effective treatments is imminent. A growing number of studies have begun to explore the feasibility of MDT in CVD, but an up-to-date systematic summary is still lacking. This review discusses the current research status of MDT from guiding magnetic fields, magnetic nanocarriers, delivery channels, drug release control, and safety assessment. The current application status of MDT in CVD is also critically introduced. On this basis, new insights into the existing problems and future optimization directions of MDT are further highlighted.
MeSH term(s)	Humans ; Cardiovascular Diseases/drug therapy ; Drug Delivery Systems ; Drug Liberation ; Magnetic Fields
Language	English
Publishing date	2023-09-13
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	1213261-5
ISSN	1521-0464 ; 1071-7544
ISSN (online)	1521-0464
ISSN	1071-7544
DOI	10.1080/10717544.2023.2256495
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Article ; Online: Comprehensive Separation Algorithm for Single-Channel Signals Based on Symplectic Geometry Mode Decomposition.

Wang, Xinyu / Zhao, Jin / Wu, Xianliang

Sensors (Basel, Switzerland)

2024 Volume 24, Issue 2

Abstract: This paper aims to explore the difficulty of obtaining source signals from complex mixed signals and the issue that the FastICA algorithm cannot directly decompose the received single-channel mixed signals and distort the signal separation in low signal- ... ...

Abstract	This paper aims to explore the difficulty of obtaining source signals from complex mixed signals and the issue that the FastICA algorithm cannot directly decompose the received single-channel mixed signals and distort the signal separation in low signal-to-noise environments. Thus, in this work, a comprehensive single-channel mixed signal separation algorithm was proposed based on the combination of Symplectic Geometry Mode Decomposition (SGMD) and the FastICA algorithm. First, SGMD-FastICA uses SGMD to decompose single-channel mixed signals, and then it uses the Pearson correlation coefficient to select the Symplectic Geometry Components that exhibit higher correlation coefficients with the mixed signals. Then, these components are expanded with the single-channel mixed signals into virtual multi-channel signals and input into the FastICA algorithm. The simulation results show that the SGMD algorithm could eliminate noise interference while keeping the raw time series unchanged, which is achievable through symplectic geometry similarity transformation during the decomposition of mixed signals. Comparative experiment results also show that compared with the EMD-FastICA and VMD-FastICA, the SGMD-FastICA algorithm has the best separation effect for single-channel mixed signals. The SGMD-FastICA algorithm represents an improved solution that addresses the limitations of the FastICA algorithm, enabling the direct separation of single-channel mixed signals, while also addressing the challenge of proper signal separation in noisy environments.
Language	English
Publishing date	2024-01-11
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s24020462
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Article ; Online: Intracellular ion accumulation in the genesis of complex action potential dynamics under cardiac diseases.

Wang, Xinyu / Landaw, Julian / Qu, Zhilin

Physical review. E

2024 Volume 109, Issue 2-1, Page(s) 24410

Abstract: Intracellular ions, including sodium (Na^{+}), calcium (Ca^{2+}), and potassium (K^{+}), etc., accumulate slowly after a change of the state of the heart, such as a change of the heart rate. The goal of this study is to understand the roles of slow ion ... ...

Abstract	Intracellular ions, including sodium (Na^{+}), calcium (Ca^{2+}), and potassium (K^{+}), etc., accumulate slowly after a change of the state of the heart, such as a change of the heart rate. The goal of this study is to understand the roles of slow ion accumulation in the genesis of cardiac memory and complex action-potential duration (APD) dynamics that can lead to lethal cardiac arrhythmias. We carry out numerical simulations of a detailed action potential model of ventricular myocytes under normal and diseased conditions, which exhibit memory effects and complex APD dynamics. We develop a low-dimensional iterated map (IM) model to describe the dynamics of Na^{+}, Ca^{2+}, and APD and use it to uncover the underlying dynamical mechanisms. The development of the IM model is informed by simulation results under the normal condition. We then use the IM model to perform linear stability analyses and computer simulations to investigate the bifurcations and complex APD dynamics, which depend on the feedback loops between APD and intracellular Ca^{2+} and Na^{+} concentrations and the steepness of the APD response to the ion concentrations. When the feedback between APD and Ca^{2+} concentration is positive, a Hopf bifurcation leading to periodic oscillatory behavior occurs as the steepness of the APD response to the ion concentrations increases. The negative feedback loop between APD and Na^{+} concentration is required for the Hopf bifurcation. When the feedback between APD and Ca^{2+} concentration is negative, period-doubling bifurcations leading to high periodicity and chaos occurs. In this case, Na^{+} accumulation plays little role in the dynamics. Finally, we carry out simulations of the detailed action potential model under two diseased conditions, which exhibit steep APD responses to ion concentrations. Under both conditions, Hopf bifurcations leading to slow oscillations or period-doubling bifurcations leading to high periodicity and chaotic APD dynamics occur, depending on the strength of the ion pump-Na^{+}-Ca^{2+} exchanger. Using functions reconstructed from the simulation data, the IM model accurately captures the bifurcations and dynamics under the two diseased conditions. In conclusion, besides using computer simulations of a detailed high-dimensional action-potential model to investigate the effects of slow ion accumulation and short-term memory on bifurcations and genesis of complex APD dynamics in cardiac myocytes under diseased conditions, this study also provides a low-dimensional mathematical tool, i.e., the IM model, to allow stability analyses for uncovering the underlying mechanisms.
MeSH term(s)	Humans ; Action Potentials/physiology ; Models, Cardiovascular ; Heart Diseases ; Myocytes, Cardiac ; Ions
Chemical Substances	Ions
Language	English
Publishing date	2024-03-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	2844562-4
ISSN	2470-0053 ; 2470-0045
ISSN (online)	2470-0053
ISSN	2470-0045
DOI	10.1103/PhysRevE.109.024410
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Article ; Online: Smart Janus cotton fabrics prepared via mist polymerization for moisture and thermal management.

Xu, Qingbo / Wang, Xinyu / Wang, Yong / Zhang, Yanyan

International journal of biological macromolecules

2024 Volume 265, Issue Pt 1, Page(s) 130929

Abstract: The construction of Janus structures on cotton fabrics can endow the fabrics with dynamic multifunctional properties. However, because of the large pores between fabric fibers, the formation of Janus structures by grafting different functional coatings ... ...

Abstract	The construction of Janus structures on cotton fabrics can endow the fabrics with dynamic multifunctional properties. However, because of the large pores between fabric fibers, the formation of Janus structures by grafting different functional coatings on the double surfaces of cotton fabrics via dipping technology is difficult. To construct Janus structures on cotton fabrics, mist polymerization and "grafting-through" polymerization technologies were used to graft polylauryl methacrylate and a heat-shrinkable thermosensitive antibacterial polymer on the inside and outside surfaces of the cotton fabric, respectively. The as-formed Janus cotton fabric demonstrated excellent antibacterial durability. Even after subjecting the Janus fabric to 70 laundering cycles, its bacterial rates against Escherichia coli and Staphylococcus aureus were > 93.0 %. Compared with the pristine cotton fabric, when the ambient temperature is high or low, the Janus fabric can adjust the skin temperature within 5 min by approximately ±3.0 °C. Additionally, the fabric exhibited excellent waterproof and moisture permeability properties. The Janus cotton fabrics prepared by the proposed strategy possess significant potential for applications in the field of wearable textiles.
MeSH term(s)	Cotton Fiber ; Silver/chemistry ; Polymerization ; Metal Nanoparticles/chemistry ; Textiles/microbiology ; Anti-Bacterial Agents/chemistry ; Escherichia coli
Chemical Substances	Silver (3M4G523W1G) ; Anti-Bacterial Agents
Language	English
Publishing date	2024-03-18
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	282732-3
ISSN	1879-0003 ; 0141-8130
ISSN (online)	1879-0003
ISSN	0141-8130
DOI	10.1016/j.ijbiomac.2024.130929
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