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Article ; Online: Enhancing the component intra- and interrelationship of Elymus nutans mono- and mixed sowing communities via adjusting sowing patterns in the Qinghai Tibetan Plateau.

Ren, Wen / Lin, Changxing / Ma, Jingyong / Zhang, Zhixin / Shen, Yuying

2024 Volume 915, Page(s) 169949

Abstract: Spatial arrangement is a key factor in maintaining community yield and stability via regulating component intra-/interspecific competition in an alpine climate environment. A 2-yr field trial was conducted on the Qinghai Tibetan Plateau, including cross ... ...

Abstract	Spatial arrangement is a key factor in maintaining community yield and stability via regulating component intra-/interspecific competition in an alpine climate environment. A 2-yr field trial was conducted on the Qinghai Tibetan Plateau, including cross row (S_C), double row (S_D), single row (S_R), broadcast (M_B), dependent row (M_D) and independent row (M_I). Our results showed that S_C could avoid intraspecific competition by reasonable spatial arrangement, which favored the dominant component growth (1st year: leaf; 2nd year: stem and reproductive organ). For mixed communities, RII (relative interaction intensity) implied that interspecific competition also embodied on dominant component, and higher Elymus nutans component advantages seriously limited Onobrychis viciifolia's components growth in the 2nd year. More details displayed that E. nutans in M_B or M_D produced the maximum system yield via increasing leaf investment at the initial stages and stem investment after July 2019. Besides, M_I possessed lower component numbers than M_B and M_D in the unit area. PCA analysis revealed that component numbers or biomasses changed synchronously, besides the E. nutans of S_C, M_B, and M_D presented significant discrepancies compared to other treatments in September 2019, which verified the effect of sowing patterns on component growth (P < 0.05), but O. viciifolia in different sowing patterns was similar in the 2nd year. Considering the adaptability and production for the environment of the Qinghai Tibetan Plateau, S_C is recommended for the promoted effect on component biomasses. M_B and M_D, with the merit of spacing utilization as well as higher resistance to variation in seasonal growth conditions via optimizing interspecific relationships for mixed communities, are adapted for increasing yield via component harvesting. Our results unveiled the potential of optimizing spatial usage efficiency via controlling component growth characteristics and stressed the importance of dynamic change of dominant components to enhance forage system production in alpine regions.
MeSH term(s)	Tibet ; Elymus ; Grassland ; Climate ; Biomass
Language	English
Publishing date	2024-01-12
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2024.169949
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Radiofrequency ablation

Li, Ming / Xu, Xiao / Qin, Yingyi / Zhang, Peng / Shen, Changxing / Xia, Qing / Fan, Lihong

Journal of Cancer

2021 Volume 12, Issue 10, Page(s) 3057–3066

Abstract: Background: ...

Abstract	Background:
Language	English
Publishing date	2021-03-19
Publishing country	Australia
Document type	Journal Article
ZDB-ID	2573318-7
ISSN	1837-9664
ISSN	1837-9664
DOI	10.7150/jca.51413
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Effects of Neuroinflammation and Autophagy on the Structure of the Blood-Brain Barrier in ADHD Model.

Fang, Zhanglu / Shen, Guanghong / Amin, Nashwa / Lou, Chengjian / Wang, Changxing / Fang, Marong

Neuroscience

2023 Volume 530, Page(s) 17–25

Abstract: Spontaneously hypertensive rats (SHR) are the most common animal model used to study attention deficit hyperactivity disorder (ADHD). The purpose of this study was to look at the impact of neuroinflammation and autophagy on blood-brain barrier function ... ...

Abstract	Spontaneously hypertensive rats (SHR) are the most common animal model used to study attention deficit hyperactivity disorder (ADHD). The purpose of this study was to look at the impact of neuroinflammation and autophagy on blood-brain barrier function in the prefrontal cortex and hippocampus of ADHD rats. The rats were separated into three groups: juvenile SHR (6 weeks), mature SHR (12 weeks), and comparable age WKY groups. An open-field test was used to assess rats' ability to move on their own. Immunofluorescence was used to detect the Iba1-immunopositive microglia, ZO-1 and TNF-α. Meanwhile, the expression of p62, Beclin-1, LC3B, and MMP9, MMP2, TNF-α, ZO-1, and occludin were detected by Western blot. The results have shown that Iba1-immunopositive microglia and TNF-α protein in the brain of SHR rats were significantly increased. Moreover, autophagy of cells and the level of MMP2 and MPP9 in the prefrontal cortex and hippocampus increased in SHR rats. In addition, the expression of ZO-1 and occludin was decreased in SHR rats. To sum up, the increase of neuroinflammation and excessive autophagy were essential factors for the damage of blood-brain barrier structure and function.
Language	English
Publishing date	2023-08-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	196739-3
ISSN	1873-7544 ; 0306-4522
ISSN (online)	1873-7544
ISSN	0306-4522
DOI	10.1016/j.neuroscience.2023.08.025
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Article: Thymalfasin therapy accelerates COVID-19 pneumonia rehabilitation through anti-inflammatory mechanisms.

Wang, Zirui / Wang, Cong / Fei, Xiaohua / Wu, Haixing / Niu, Peiqin / Shen, Changxing

Pneumonia (Nathan Qld.)

2023 Volume 15, Issue 1, Page(s) 14

Abstract: Introduction: Thymosin drugs are commonly used for the treatment of viral infections due to their immunomodulatory effects. The comprehensive clinical efficacy of Thymalfasin therapy for COVID-19 associated pneumonia is not yet fully researched, another ...

Abstract	Introduction: Thymosin drugs are commonly used for the treatment of viral infections due to their immunomodulatory effects. The comprehensive clinical efficacy of Thymalfasin therapy for COVID-19 associated pneumonia is not yet fully researched, another issue, whether the use of thymosin drugs can reduce the rate of COVID-19 progression to severe pneumonia has not been well documented. The aim of the present study was to multi-angle evaluate the clinical efficacy of Thymalfasin therapy for COVID-19 pneumonia by retrospective review of the clinical data of 338 inpatients with common COVID-19 infection who received treatment in our hospital. Methods: The primary index of observation was whether progression to severe pneumonia occurred within a week after admission, and the secondary indexes were the length of hospital stay, time of negative conversion of COVID-19 antigen, the number of peripheral lymphocytes and white blood cells (WBC), and C-reactive protein (CRP) and procalcitonin (PCT) levels,and the control of pneumonia related symptoms, for example, fever, listlessness, inflammatory exudate area shown on lung CT (%). Results: The length of hospital stay of patients in Thymalfasin group was significantly shorter than that of patients in the control group (p < 0.01). The proportion of relief of pneumonia related symptoms (fever, fatigue) in the Thymalfasin therapy group was significantly higher than that in the control group, and the inflammatory exudate area shown on CT was significantly lower than that in the control group (p < 0.05). Multivariate logistic regression analysis showed that the use of Thymalfasin was an independent protective factor affecting the progression to severe pneumonia. Multifactorial Cox model analysis indicated that negative conversion of COVID-19 antigen was significantly faster in patients using Thymalfasin and younger patients. Conclusion: Thymalfasin therapy has shown excellent clinical efficacy in the treatment of COVID-19 pneumonia, it can reduce inflammatory reactions, promote the relief of COVID-19 pneumonia related symptoms such as fever and fatigue, facilitate effusion absorption, and accelerate COVID-19 pneumonia recovery. Thymalfasin can prevent progression of common COVID-19 infection to severe pneumonia via multiple immunity-enhancing and anti-inflammatory protective mechanisms.
Language	English
Publishing date	2023-09-25
Publishing country	England
Document type	Journal Article
ZDB-ID	2803296-2
ISSN	2200-6133
ISSN	2200-6133
DOI	10.1186/s41479-023-00116-6
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Immunomodulatory effects of intestinal lung axis microecology and other factors on the prognosis of advanced non-small cell lung cancer.

Shen, Changxing / Ren, Yanbei / Zhang, Xu / Xia, Qing / Li, Ming / Wang, Changhui / Fan, Lihong

Translational cancer research

2022 Volume 8, Issue 5, Page(s) 2205–2210

Abstract: Overall survival (OS) of lung cancer varies greatly with individual patients in the global setting. Multiple factors may affect the prognosis. Different antibiotics have significant effects on the prognosis of lung cancer patients. The intestinal ... ...

Abstract	Overall survival (OS) of lung cancer varies greatly with individual patients in the global setting. Multiple factors may affect the prognosis. Different antibiotics have significant effects on the prognosis of lung cancer patients. The intestinal microbiome, nutritional status and inflammatory factors all have significant impact on OS of lung cancer patients.
Language	English
Publishing date	2022-01-15
Publishing country	China
Document type	Journal Article ; Review
ZDB-ID	2901601-0
ISSN	2219-6803 ; 2218-676X
ISSN (online)	2219-6803
ISSN	2218-676X
DOI	10.21037/tcr.2019.09.32
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Article ; Online: Information Perception Method for Fruit Trees Based on 2D LiDAR Sensor

Yong Wang / Changxing Geng / Guofeng Zhu / Renyuan Shen / Haiyang Gu / Wanfu Liu

Agriculture, Vol 12, Iss 7, p

2022 Volume 914

Abstract: To solve the problem of orchard environmental perception, a 2D LiDAR sensor was used to scan fruit trees on both sides of a test platform to obtain their position. Firstly, the two-dimensional iterative closest point (2D-ICP) algorithm was used to obtain ...

Abstract	To solve the problem of orchard environmental perception, a 2D LiDAR sensor was used to scan fruit trees on both sides of a test platform to obtain their position. Firstly, the two-dimensional iterative closest point (2D-ICP) algorithm was used to obtain the complete point cloud data of fruit trees on both sides. Then, combining the lightning connection algorithm (LAPO) and the density-based clustering algorithm (DBSCAN), a fruit tree detection method based on density-based lightning connection clustering (LAPO-DBSCAN) was proposed. After obtaining the point cloud data of fruit trees on both sides of the test platform using the 2D-ICP algorithm, the LAPO-DBSCAN algorithm was used to obtain the position of fruit trees. The experimental results show that the positive detection rate was 96.69%, the false detection rate was 3.31%, and the average processing time was 1.14 s, verifying the reliability of the algorithm. Therefore, this algorithm can be used to accurately find the position of fruit trees, meaning that it can be applied to orchard navigation in a later stage.
Keywords	point cloud registration of fruit trees ; lightning attachment procedure optimization ; density-based spatial clustering of applications with noise ; information perception of fruit trees ; Agriculture (General) ; S1-972
Subject code	519
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Establishment of a malignancy and benignancy prediction model of sub-centimeter pulmonary ground-glass nodules based on the inflammation-cancer transformation theory.

Shen, Changxing / Wu, Qiong / Xia, Qing / Cao, Chuanwu / Wang, Fei / Li, Zhuang / Fan, Lihong

Frontiers in medicine

2022 Volume 9, Page(s) 1007589

Abstract: Background: In recent years, Chinese clinicians are frequently encountered by patients with multiple lung nodules and these intensity ground-glass nodules (GGNs) are usually small in size and some of them have no spicule sign. In addition, early lung ... ...

Abstract	Background: In recent years, Chinese clinicians are frequently encountered by patients with multiple lung nodules and these intensity ground-glass nodules (GGNs) are usually small in size and some of them have no spicule sign. In addition, early lung cancer is diagnosed in large numbers of non-heavy smokers and individuals with no caner history. Obviously, the Mayo model is not applicable to these patients. The aim of the present study is to develop a new and more applicable model that can predict malignancy or benignancy of pulmonary GGNs based on the inflammation-cancer transformation theory. Materials and methods: Included in this study were patients who underwent surgical resection or lung puncture biopsy of GGNs in Shanghai 10th People's Hospital between January 1, 2018 and May 31, 2021 with the inclusion criterion of the maximum diameter of GGN < 1.0 cm. All the included patients had their pulmonary GGNs diagnosed by postoperative pathology. The patient data were analyzed to establish a prediction model and the predictive value of the model was verified. Results: Altogether 100 GGN patients who met the inclusion criteria were included for analysis. Based on the results of logistic stepwise regression analysis, a mathematical predication equation was established to calculate the malignancy probability as follows: Malignancy probability rate (p) = ex/(1 + ex); Conclusion: By focusing on four major factors (chronic inflammation history, human Th cell, imaging vascular convergence sign and mGGNs), the present prediction model greatly improves the accuracy of malignancy or benignancy prediction of sub-centimeter pulmonary GGNs. This is a breakthrough innovation in this field.
Language	English
Publishing date	2022-10-05
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2775999-4
ISSN	2296-858X
ISSN	2296-858X
DOI	10.3389/fmed.2022.1007589
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Article ; Online: Study on the Fluidization Quality Characterization Method and Process Intensification of Fine Coal Separation in a Vibrated Dense Medium Fluidized Bed

Enhui Zhou / Yadong Shan / Linhai Li / Fanshun Shen / Enkhsaruul Byambajav / Bo Zhang / Changxing Shi

ACS Omega, Vol 6, Iss 22, Pp 14268-

2021 Volume 14277

Keywords	Chemistry ; QD1-999
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	American Chemical Society
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?

Wang, Fei / Ding, Liang / Rao, Jun / Liu, Ye / Shen, Li / Ding, Changxing

2023

Abstract: The multimedia community has shown a significant interest in perceiving and representing the physical world with multimodal pretrained neural network models, and among them, the visual-language pertaining (VLP) is, currently, the most captivating topic. ... ...

Abstract	The multimedia community has shown a significant interest in perceiving and representing the physical world with multimodal pretrained neural network models, and among them, the visual-language pertaining (VLP) is, currently, the most captivating topic. However, there have been few endeavors dedicated to the exploration of 1) whether essential linguistic knowledge (e.g., semantics and syntax) can be extracted during VLP, and 2) how such linguistic knowledge impact or enhance the multimodal alignment. In response, here we aim to elucidate the impact of comprehensive linguistic knowledge, including semantic expression and syntactic structure, on multimodal alignment. Specifically, we design and release the SNARE, the first large-scale multimodal alignment probing benchmark, to detect the vital linguistic components, e.g., lexical, semantic, and syntax knowledge, containing four tasks: Semantic structure, Negation logic, Attribute ownership, and Relationship composition. Based on our proposed probing benchmarks, our holistic analyses of five advanced VLP models illustrate that the VLP model: i) shows insensitivity towards complex syntax structures and relies on content words for sentence comprehension; ii) demonstrates limited comprehension of combinations between sentences and negations; iii) faces challenges in determining the presence of actions or spatial relationships within visual information and struggles with verifying the correctness of triple combinations. We make our benchmark and code available at \url{https://github.com/WangFei-2019/SNARE/}. Comment: [TL;DR] we design and release the SNARE, the first large-scale multimodal alignment probing benchmark for current vision-language pretrained models
Keywords	Computer Science - Multimedia ; Computer Science - Artificial Intelligence ; Computer Science - Computation and Language ; Computer Science - Computer Vision and Pattern Recognition
Subject code	400
Publishing date	2023-08-24
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Information Perception Method for Fruit Trees Based on 2D LiDAR Sensor

Wang, Yong / Geng, Changxing / Zhu, Guofeng / Shen, Renyuan / Gu, Haiyang / Liu, Wanfu

Agriculture (Basel). 2022 June 23, v. 12, no. 7

2022

Abstract	To solve the problem of orchard environmental perception, a 2D LiDAR sensor was used to scan fruit trees on both sides of a test platform to obtain their position. Firstly, the two-dimensional iterative closest point (2D-ICP) algorithm was used to obtain the complete point cloud data of fruit trees on both sides. Then, combining the lightning connection algorithm (LAPO) and the density-based clustering algorithm (DBSCAN), a fruit tree detection method based on density-based lightning connection clustering (LAPO-DBSCAN) was proposed. After obtaining the point cloud data of fruit trees on both sides of the test platform using the 2D-ICP algorithm, the LAPO-DBSCAN algorithm was used to obtain the position of fruit trees. The experimental results show that the positive detection rate was 96.69%, the false detection rate was 3.31%, and the average processing time was 1.14 s, verifying the reliability of the algorithm. Therefore, this algorithm can be used to accurately find the position of fruit trees, meaning that it can be applied to orchard navigation in a later stage.
Keywords	agriculture ; algorithms ; data collection ; fruit trees ; fruits ; lidar ; lightning ; orchards
Language	English
Dates of publication	2022-0623
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2651678-0
ISSN	2077-0472
ISSN	2077-0472
DOI	10.3390/agriculture12070914
Database	NAL-Catalogue (AGRICOLA)

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