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Article ; Online: Alpine Grassland Reviving Response to Seasonal Snow Cover on the Tibetan Plateau

Ying Ma / Xiaodong Huang / Qisheng Feng / Tiangang Liang

Remote Sensing, Vol 14, Iss 2499, p

2022 Volume 2499

Abstract: Season snow cover plays an important role in vegetation growth in alpine regions. In this study, we analyzed the spatial and temporal variations in seasonal snow cover and the start of the growing season (SOS) of alpine grasslands and preliminarily ... ...

Abstract	Season snow cover plays an important role in vegetation growth in alpine regions. In this study, we analyzed the spatial and temporal variations in seasonal snow cover and the start of the growing season (SOS) of alpine grasslands and preliminarily studied the mechanism by which snow cover affects SOS changes by modifying the soil temperature (ST) and soil moisture (SM) in spring. The results showed that significant interannual trends in the SOS, snow end date (SED), snow cover days (SCD), ST, and SM existed over the Tibetan Plateau (TP) in China from 2000 to 2020. The SOS advanced by 2.0 d/10 a over the TP over this period. Moreover, the SOS showed advancing trends in the eastern and central parts of the TP and a delayed trend in the west. The SED and SCD exhibited an advancing trend and a decreasing trend in high-elevation areas, respectively, and the opposite trends in low-elevation areas. The ST showed a decreasing trend in low-elevation areas and an increasing trend in high-elevation areas. The SM tended to increase in most areas. The effects of the seasonal snow cover on the ST and SM indirectly influenced the SOS of alpine grasslands. The delayed SEDs and more SCD observed herein could provide increasingly wet soil conditions optimal for the advancement of the SOS, while less snow and shorter snow seasons could delay the SOS of alpine grasslands on the TP.
Keywords	snow melting ; alpine grassland ; remote sensing ; Tibetan Plateau ; Science ; Q
Subject code	910
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Three-Dimensional Spatial Distribution and Influential Factors of Soil Total Nitrogen in a Coal Mining Subsidence Area

Huijuan Zhang / Wenkai Liu / Qiuxia Zhang / Xiaodong Huang

Sustainability, Vol 14, Iss 13, p

2022 Volume 7897

Abstract: Soil nitrogen is very important for crop growth and development. However, the factors affecting the three-dimensional spatial distribution of soil total nitrogen (TN), particularly in coal mining subsidence areas, are unclear. In this study, Markov ... ...

Abstract	Soil nitrogen is very important for crop growth and development. However, the factors affecting the three-dimensional spatial distribution of soil total nitrogen (TN), particularly in coal mining subsidence areas, are unclear. In this study, Markov geostatistics was used to analyse the three-dimensional spatial distribution characteristics and influential factors of TN by examining 180 soil samples from the Zhaogu mine in China. The results showed that the TN content was significantly different at different soil depths (0–20, 20–40, 40–60 cm) and decreased with increasing soil depth. The variation coefficient of the TN content decreased gradually from top to bottom, ranging from 18.18 to 25.62%. In addition, the TN content was greatly affected by mining subsidence, rainfall, irrigation, fertilization and management mode. The factors that influenced the TN content also varied across different slope positions. The TN content of the upslope was the highest, and the TN content of the middle slope was the lowest. These results can provide research ideas and technical countermeasures for ecological environment improvement and sustainable land development in coal mining subsidence areas.
Keywords	soil total nitrogen ; soil spatial variability ; coal mining subsidence ; Markov chain ; influencing factor ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
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 ; Online: Chinese stroke patients with atrial fibrillation used Robert's age-adjusted warfarin loading protocol obtained good INR results within therapeutic range

Weiliang Luo / Xuanwen Luo / Suqin Chen / Jiming Li / Xiaodong Huang / Yu Rao / Wengsheng Xu

Scientific Reports, Vol 13, Iss 1, Pp 1-

2023 Volume 9

Abstract: Abstract To assess whether Roberts’ age-adjusted warfarin loading protocol is effective in Chinese patients and whether the SAMeTT2R2 score can predict international normalized ratio (INR) control. Roberts’ protocol for warfarin titration was applied to ... ...

Abstract	Abstract To assess whether Roberts’ age-adjusted warfarin loading protocol is effective in Chinese patients and whether the SAMeTT2R2 score can predict international normalized ratio (INR) control. Roberts’ protocol for warfarin titration was applied to patients with non-valvular atrial fibrillation (NVAF) complicated with ischemic stroke at the Department of Neurology between 2014 and 2019. Clinical and sociodemographic variables were recorded. A minimum of 1-year follow-up was used to calculate the time in therapeutic range (TTR) of the INR. A total of 94 acute ischemic stroke patients with NVAF were included in the study. Seventy-seven (81.9%) of the patients had attained stable INR (2.0–3.0) at the fifth dose, and 90.0% of the patients had achieved stable INR on the ninth day. Seventeen (18.1%) of the patients had an INR > 4 during dose-adjustment period. Patients with INR > 4 had significantly lower body weight (53.8 vs. 63.1 kg, P = 0.014), lower rate of achievement of stable INR (35.3% vs. 92.2%, P = 0.000), and lower rate of TTR ≥ 65% (23.5% vs. 70.1%, P = 0.001), but with no significant increase in bleeding risk. A total of 89 patients underwent long-term INR follow-up, of which 58 (65.2%) patients achieved TTR ≥ 65%. Patients with poor TTR had significantly lower body weight (56.3 vs. 63.7 kg, P = 0.020) and lower rate of stable INR achievement (64.5% vs. 89.7%, P = 0.002). All 94 patients had SAMeTT2R2 score ≥ 2. There was no linear association between SAMeTT2R2 score and the rate of TTR ≥ 65% (P trend = 0.095). Chinese ischemic stroke patients with NVAF on warfarin can safely and quickly achieve therapeutic INR using Roberts’ age-adjusted protocol and can obtain a good TTR. Lower body weight may be a predictor of poor TTR and INR > 4. Patients who have not attained stable INR after adjusting the dose five times are at high risk for poor TTR. SAMeTT2R2 score may not predict TTR in Chinese ischemic stroke patients with NVAF.
Keywords	Medicine ; R ; Science ; Q
Subject code	616 ; 610
Language	English
Publishing date	2023-10-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Cooling water intake system safety analysis based on impingement probability

Xiaocheng Fu / Fenglei Du / Xiaodong Huang / Juan Pei / Zhenglou Zhang / Xiaofeng Xing / Xiang Pu

Frontiers in Marine Science, Vol

2023 Volume 10

Abstract: Invasion or aggregation of marine organisms in cooling water intake systems (CWIS) has gradually become an important problem affecting the safety of nuclear power plants with environmental and climate changes. In this study, a 3-dimensional numerical ... ...

Abstract	Invasion or aggregation of marine organisms in cooling water intake systems (CWIS) has gradually become an important problem affecting the safety of nuclear power plants with environmental and climate changes. In this study, a 3-dimensional numerical model (TELEMAC-3D) was used to determine the impingement probability in a typical nuclear power plant with a once-through cooling system, and the effect on CWIS safety. The factors controlling impingement probability were also analyzed. Results show that (1) impingement probability decreased rapidly with an increase in distance from the CWIS. In addition, the distance of the impingement effect of a nuclear power plant with six units was mainly within 1 km of the CWIS. (2) Impingement probability increased with water withdrawal, and as distance to the CWIS increased, the increase in probability increased. (3) Generally, an increase in tide strength led to a decrease impingement probability. (4) Near the CWIS, the impingement probabilities of areas upstream or downstream of the CWIS along the tidal flow direction were much higher than those not in those areas. (5) An increase in water depth significantly reduced impingement probability. When the water depth of the CWIS increased from 5 m to 15 m, impingement probability was reduced up to 30%. Based on the above findings, the following suggestions were made to minimize the impingement effects on CWIS safety: first, the CWIS of coastal nuclear power plants should be set in an area with low aquatic biomass, strong tides, deep water, and few surface species within the range of 1 km, and second, the amount of cooling water withdrawal or velocity should be reduced as much as possible.
Keywords	cooling water intake system ; impingement probability ; impact factors ; numerical modeling ; TELEMAC ; nuclear power plant ; Science ; Q ; General. Including nature conservation ; geographical distribution ; QH1-199.5
Subject code	580
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Bone marrow mesenchymal stem cell-derived exosomal microRNA regulates microglial polarization

Xianwei Huang / Xiong Liu / Jiaqi Zeng / Penghui Du / Xiaodong Huang / Jiyan Lin

PeerJ, Vol 11, p e

2023 Volume 16359

Abstract: Objective This study aimed to explore the effects of bone marrow mesenchymal stem cell (BMSC)-derived exosomal miR-146a-5p on microglial polarization and the potential underlying mechanisms in oxygen-glucose deprivation (OGD)-exposed microglial cells. ... ...

Abstract	Objective This study aimed to explore the effects of bone marrow mesenchymal stem cell (BMSC)-derived exosomal miR-146a-5p on microglial polarization and the potential underlying mechanisms in oxygen-glucose deprivation (OGD)-exposed microglial cells. Methods Exosomes were isolated from BMSCs, and their characteristics were examined. The effects of BMSC-derived exosomes on microglial polarization were investigated in OGD-exposed BV-2 cells. Differentially expressed miRNAs were identified and their biological function was explored using enrichment analyses. The regulatory role of miR-146a-5p in microglial polarization was studied via flow cytometry. Finally, the downstream target gene Traf6 was validated, and the role of the miR-146a-5p/Traf6 axis in modulating microglial polarization was investigated in OGD-exposed BV-2 cells. Results BMSC-derived exosomes were successfully isolated and characterized. A total of 10 upregulated and 33 downregulated miRNAs were identified. Exosomal treatment resulted in significant changes in microglial polarization markers. miR-146a-5p was found to be significantly downregulated in OGD-exposed microglial cells treated with exosomes. Manipulation of miR-146a-5p expression modulated microglial polarization. Moreover, the miR-146a-5p/Traf6 axis regulated microglial polarization. Conclusion Our findings demonstrate that BMSC-derived exosomal via miR-146a-5p modulates microglial polarization by targeting Traf6, providing a potential thermal target for the treatment of neurological diseases involving microglial activation.
Keywords	Microglial cell ; Polarization ; Exosomes ; Bone marrow mesenchymal stem cell ; MiR-146a-5p ; Traf6 ; Medicine ; R ; Biology (General) ; QH301-705.5
Subject code	500
Language	English
Publishing date	2023-11-01T00:00:00Z
Publisher	PeerJ Inc.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Soil Moisture Retrieval Using SAR Backscattering Ratio Method during the Crop Growing Season

Minfeng Xing / Lin Chen / Jinfei Wang / Jiali Shang / Xiaodong Huang

Remote Sensing, Vol 14, Iss 13, p

2022 Volume 3210

Abstract: Soil moisture content (SMC) is an indispensable basic element for crop growth and development in agricultural production. Obtaining accurate information on SMC in real time over large agricultural areas has important guiding significance for crop yield ... ...

Abstract	Soil moisture content (SMC) is an indispensable basic element for crop growth and development in agricultural production. Obtaining accurate information on SMC in real time over large agricultural areas has important guiding significance for crop yield estimation and production management. In this study, the paper reports on the retrieval of SMC from RADARSAT-2 polarimetric SAR data. The proposed SMC retrieval algorithm includes vegetation correction based on a ratio method and roughness correction based on the optimal roughness method. Three vegetation description parameters (i.e., RVI, LAI, and NDVI) serve as vegetation descriptors in the parameterization of the algorithm. To testify the vegetation correction result of the algorithm, the water cloud model (WCM) was compared with the algorithm. The calibrated integrated equation model (CIEM) was employed to describe the backscattering from the underlying soil. To improve the accuracy of SMC retrieval, the CIEM model was optimized by using the optimal roughness parameter and the normalization method of reference incidence angle. Validation against ground measurements showed a high correlation between the measured and estimated SMC when the NDVI serves as vegetation descriptor (R 2 = 0.68, RMSE = 4.15 vol.%, p < 0.01). The overall estimation performance of the proposed SMC retrieval algorithm is better than that of the WCM. It demonstrates that the proposed algorithm has an operational potential to estimate SMC over wheat fields during the growing season.
Keywords	soil moisture content ; ratio method ; WCM ; CIEM ; RADARSAT-2 SAR ; Science ; Q
Subject code	550
Language	English
Publishing date	2022-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Adulteration Detection and Quantification in Olive Oil Using Excitation-Emission Matrix Fluorescence Spectroscopy and Chemometrics.

Lujun, Zhang / Nuo, Cai / Xiaodong, Huang / Xinmin, Fan / Juanjuan, Gao / Jin, Gao / Sensen, Li / Yan, Wang / Chunyan, Wang

Journal of fluorescence

2024

Abstract: This research investigates the use of excitation-emission matrix fluorescence (EEMF) in conjunction with chemometric models to rapidly identify and quantify adulteration in olive oil, a critical concern where sample availability is limited. Adulteration ... ...

Abstract	This research investigates the use of excitation-emission matrix fluorescence (EEMF) in conjunction with chemometric models to rapidly identify and quantify adulteration in olive oil, a critical concern where sample availability is limited. Adulteration is simulated by blending soybean, peanut, and linseed oils into olive oil, creating diverse adulterated samples. Principal component analysis (PCA) was applied to the EEMF spectral data as an initial exploratory measure to cluster and differentiate adulterated samples. Spatial clustering enabled vivid visualization of the variations and trends in the spectra. The novel application of parallel factor analysis (PARAFAC) for data decomposition in this paper focuses on unraveling correlations between the decomposed components and the actual adulterated components, which offers a novel perspective for accurately quantifying adulteration levels. Additionally, a comparative analysis was conducted between the PCA and PARAFAC methodologies. Our study not only unveils a new avenue for the quantitative analysis of adulterants in olive oil through spectral detection but also highlights the potential for applying these insights in practical, real-world scenarios, thereby enhancing detection capabilities for various edible oil samples. This promises to improve the detection of adulteration across a range of edible oil samples, offering significant contributions to food safety and quality assurance.
Language	English
Publishing date	2024-03-08
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2016892-5
ISSN	1573-4994 ; 1053-0509
ISSN (online)	1573-4994
ISSN	1053-0509
DOI	10.1007/s10895-024-03613-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: MODIS Fractional Snow Cover Mapping Using Machine Learning Technology in a Mountainous Area

Changyu Liu / Xiaodong Huang / Xubing Li / Tiangang Liang

Remote Sensing, Vol 12, Iss 6, p

2020 Volume 962

Abstract: To improve the poor accuracy of the MODIS (Moderate Resolution Imaging Spectroradiometer) daily fractional snow cover product over the complex terrain of the Tibetan Plateau (RMSE = 0.30), unmanned aerial vehicle and machine learning technologies are ... ...

Abstract	To improve the poor accuracy of the MODIS (Moderate Resolution Imaging Spectroradiometer) daily fractional snow cover product over the complex terrain of the Tibetan Plateau (RMSE = 0.30), unmanned aerial vehicle and machine learning technologies are employed to map the fractional snow cover based on MODIS over this terrain. Three machine learning models, including random forest, support vector machine, and back-propagation artificial neural network models, are trained and compared in this study. The results indicate that compared with the MODIS daily fractional snow cover product, the introduction of a highly accurate snow map acquired by unmanned aerial vehicles as a reference into machine learning models can significantly improve the MODIS fractional snow cover mapping accuracy. The random forest model shows the best accuracy among the three machine learning models, with an RMSE (root-mean-square error) of 0.23, especially over forestland and shrubland, with RMSEs of 0.13 and 0.18, respectively. Although the accuracy of the support vector machine and back-propagation artificial neural network models are worse over forestland and shrubland, their average errors are still better than that of MOD10A1. Different fractional snow cover gradients also affect the accuracy of the machine learning algorithms. Nevertheless, the random forest model remains stable in different fractional snow cover gradients and is, therefore, the best machine learning algorithm for MODIS fractional snow cover mapping in Tibetan Plateau areas with complex terrain and severely fragmented snow cover.
Keywords	modis ; fractinal snow cover ; uav ; tibetan plateau ; Science ; Q
Subject code	006
Language	English
Publishing date	2020-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: ANTXR1 Is a Prognostic Biomarker and Correlates With Stromal and Immune Cell Infiltration in Gastric Cancer

Xiaodong Huang / Jie Zhang / Yongbin Zheng

Frontiers in Molecular Biosciences, Vol

2020 Volume 7

Abstract: Gastric cancer (GC) is a complex and heterogeneous disease, making it difficult to ascertain the optimal therapeutic approach for individual GC patients. Stromal and immune cell infiltration in GC has a strong correlation with clinical outcomes; however, ...

Abstract	Gastric cancer (GC) is a complex and heterogeneous disease, making it difficult to ascertain the optimal therapeutic approach for individual GC patients. Stromal and immune cell infiltration in GC has a strong correlation with clinical outcomes; however, the underlying mechanisms that drive immunosuppression remain vastly undiscovered. Recent studies validated that anthrax toxin receptor 1 (ANTXR1) is aberrantly expressed in several cancers and holds promise as a new therapeutic target for cancer. However, its immunological roles in GC are still unclear. Here, we show that we identify the distinct stromal and immune cell infiltration in GC between the high and low ANTXR1 expression group by analyzing genomic data. Clinically, ANTXR1 is highly expressed in GC and correlates with adverse clinicopathological characteristics. Additionally, high ANTXR1 expression is linked to markedly poor clinical outcomes and resistance to chemotherapy, whereas the low ANTXR1 expression group is correlated with better outcomes and response to chemotherapy in GC patients. We further revealed the differential landscape of somatic tumor mutation burden (TMB) between the two groups and observed that patients with high ANTXR1 expression suffered from a lower TMB, potentially leading to less sensitivity to checkpoint therapy. Molecularly, results displayed that ANTXR1 is an immunosuppressive element, which may perform its function via promoting the secretion of immunosuppressive factors that play a significant role in modulating tumor-associated fibroblast transformation, M2 macrophage polarization, and T cell exhaustion. Gene set enrichment analysis revealed that cancer-related pathways including epithelial-to-mesenchymal transition, focal adhesion, and transforming growth factor-β (TGF-β) signaling pathways were enriched in high ANTXR1 expression tumors. Our work suggests that ANTXR1 could not only serve as a valuable prognostic biomarker in GC but also be deemed as a potential immunotherapeutic target and useful biomarker of ...
Keywords	gastric cancer ; immune infiltration ; immunotherapy ; bioinfomatics ; ANTXR1 ; Biology (General) ; QH301-705.5
Subject code	610
Language	English
Publishing date	2020-12-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Estimating Soil Moisture over Winter Wheat Fields during Growing Season Using RADARSAT-2 Data

Lin Chen / Minfeng Xing / Binbin He / Jinfei Wang / Min Xu / Yang Song / Xiaodong Huang

Remote Sensing, Vol 14, Iss 2232, p

2022 Volume 2232

Abstract: Soil moisture content (SMC) is a significant factor affecting crop growth and development. However, SMC estimation, based on synthetic aperture radar (SAR), is influenced by a variety of surface parameters, such as vegetation cover and surface roughness. ...

Abstract	Soil moisture content (SMC) is a significant factor affecting crop growth and development. However, SMC estimation, based on synthetic aperture radar (SAR), is influenced by a variety of surface parameters, such as vegetation cover and surface roughness. As a result, determining the SMC across agricultural areas (e.g., wheat fields) remotely (i.e., without ground measurement) is difficult to achieve. In this study, a model-based polarization decomposition method was used to decompose the original SAR signal into different scattering components that represented different scattering mechanisms. The different volume scattering models were applied, and then the results were compared in order to remove the scattering contribution from vegetation canopy, and extract the surface scattering components related to the soil moisture. Finally, by combining extensively used surface scattering models (e.g., CIEM and Dubois), and a method of roughness parameters optimization, a lookup table was developed to estimate the soil moisture during the wheat growth period. When CIEM is applied, the R 2 and RMSE of the SMC are 0.534, 5.62 vol.%, and for the Dubois model, 0.634, 5.16 vol.%, respectively, which indicates that this approach provides good estimation performance for measuring soil moisture during the wheat growing season.
Keywords	soil moisture ; polarization decomposition ; CIEM ; Dubois model ; RADARSAT-2 ; Science ; Q
Subject code	550
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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