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Article ; Online: Two-End-Member Mixing in the Fluids Emitted From Mud Volcano Lei-Gong-Huo, Eastern Taiwan

Hung-Chun Chao / Chen-Feng You / In-Tian Lin / Hou-Chun Liu / Ling-Ho Chung / Chun-Chang Huang / Chuan-Hsiung Chung

Frontiers in Earth Science, Vol

Evidence From Sr Isotopes

2022 Volume 9

Abstract: ... at depth. Mud volcano Lei-Gong-Huo (MV LGH) is a unique mud volcano, which is located on the mélange ...

Abstract	Mud volcano is one of the most important conduits for deep seated materials to migrate upward in sedimentary basins, convergent margins, and subduction zones. Understanding their temporal and spatial characteristics and variations provides us the important information on fluid sources and chemical compositions at depth. Mud volcano Lei-Gong-Huo (MV LGH) is a unique mud volcano, which is located on the mélange formation lying on the andesitic volcanic arc. Fluids emitted from 46 mud pools in MV LGH in eastern Taiwan were sampled and their major trace constitutes as well as H, O, and Sr isotopes (87Sr/86Sr and δ88Sr) were measured. Major constitutes of the fluids are Cl−, Na, and Ca. Compared with seawater, LGH fluids have lower Cl−, δD, δ18O, Na/Cl, K/Cl, and Mg/Cl but higher Ca/Cl ratios, indicating water–rock interaction of igneous rock and the ancient seawater at the source region. This interpretation is further supported by Sr isotopes, which show low value of 87Sr/86Sr ratio down to 0.70708. The result of spatial distribution showing strong negative correlation between Na and Ca concentration as well as Ca and 87Sr/86Sr ratios indicates that two end-member mixing is the major chemical characteristic. The fluids interacting with igneous rock carry high Ca, high δ88Sr, low Na, and low 87Sr/86Sr ratio, while those interacting with sedimentary rock carry low Ca, low δ88Sr, high Na, and high 87Sr/86Sr ratio. The source from the igneous region dominates the eastern and southeastern parts of the mud pools while sedimentary source dominates the western and northwestern parts. Most mud pools show mixing behavior between the two sources. Some of the sedimentary-dominated mud pools reveal existence of residual ancient water as indicated by 87Sr/86Sr. The major factor to fractionate the stable Sr isotopes in LGH waters is the source lithology. In summary, fluids emitted by mud pools in LGH originate from two sources, which are water–rock interactions of igneous rock with the ancient seawater from the east and sedimentary rock from the west at depth, resulting from the complex geologic background of mélange formation.
Keywords	mud volcano ; radiogenic Sr isotopes ; stable Sr isotopes ; sediment-hosted geothermal systems ; water–rock interaction ; Science ; Q
Subject code	550
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: A network pharmacology-based approach to explore the active ingredients and molecular mechanism of Lei-gong-gen formula granule on a spontaneously hypertensive rat model.

Li, Qiaofeng / Lan, Taijin / He, Songhua / Chen, Weiwei / Li, Xiaolan / Zhang, Weiquan / Liu, Ying / Zhang, Qiuping / Chen, Xin / Han, Yaoyao / Su, Zhiheng / Zhu, Dan / Guo, Hongwei

Chinese medicine

2021 Volume 16, Issue 1, Page(s) 99

Abstract: Background: Lei-gong-gen formula granule (LFG) is a folk prescription derived from Zhuang ...

Abstract	Background: Lei-gong-gen formula granule (LFG) is a folk prescription derived from Zhuang nationality, the largest ethnic minority among 56 nationalities in China. It consists of three herbs, namely Eclipta prostrata (L.) L., Smilax glabra Roxb, and Centella asiatica (L.) Urb. It has been widely used as health protection tea for hundreds of years to prevent hypertension in Guangxi Zhuang Autonomous Region. The purpose of this study is to validate the antihypertensive effect of LFG on the spontaneously hypertensive rat (SHR) model, and to further identify the effective components and anti-hypertension mechanism of LFG. Methods: The effects of LFG on blood pressure, body weight, and heart rate were investigated in vivo using the SHR model. The levels of NO, ANG II, and ET-1 in the serum were measured, and pathological changes in the heart were examined by H&E staining. The main active components of LFG, their corresponding targets, and hypertension associated pathways were discerned through network pharmacology analysis based on the Traditional Chinese Medicine Systems Pharmacology (TCMSP), Traditional Chinese Medicine Integrated Database (TCMID), and the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM). Then the predicted results were further verified by molecular biology experiments such as RT-qPCR and western blot. Additionally, the potential active compounds were predicted by molecular docking technology, and the chemical constituents of LFG were analyzed and identified by UPLC-QTOF/MS technology. Finally, an in vitro assay was performed to investigate the protective effects of potential active compounds against hydrogen peroxide (H Results: LFG could effectively reduce blood pressure and increase serum NO content in SHR model. Histological results showed that LFG could ameliorate pathological changes such as cardiac hypertrophy and interstitial inflammation. From network pharmacology analysis, 53 candidate active compounds of LFG were collected, which linked to 765 potential targets, and 828 hypertension associated targets were retrieved, from which 12 overlapped targets both related to candidate active compounds from LFG and hypertension were screened and used as the potential targets of LFG on antihypertensive effect. The molecular biology experiments of the 12 overlapped targets showed that LFG could upregulate the mRNA and protein expressions of NOS3 and proto-oncogene tyrosine-protein kinase SRC (SRC) in the thoracic aorta. Pathway enrichment analysis showed that the PI3K-AKT signaling pathway was closely related to the expression of NOS3 and SRC. Moreover, western blot results showed that LFG significantly increased the protein expression levels of PI3K and phosphorylated AKT in SHR model, suggesting that LFG may active the PI3K-AKT signaling pathway to decrease hypertension. Molecular docking study further supported that p-hydroxybenzoic acid, cedar acid, shikimic acid, salicylic acid, nicotinic acid, linalool, and histidine can be well binding with NOS3, SRC, PI3K, and AKT. UPLC-QTOF/MS analysis confirmed that p-hydroxybenzoic acid, shikimic acid, salicylic acid, and nicotinic acid existed in LFG. Pre-treatment of HUVEC with nicotinic acid could alleviate the effect on cell viability induced by H Conclusions: LFG can reduce the blood pressure in SHR model, which might be attributed to increasing the NO level in serum for promoting vasodilation via upregulating SRC expression level and activating the PI3K-AKT-NOS3 signaling pathway. Nicotinic acid might be the potential compound for LFG antihypertensive effect.
Language	English
Publishing date	2021-10-09
Publishing country	England
Document type	Journal Article
ZDB-ID	2260322-0
ISSN	1749-8546
ISSN	1749-8546
DOI	10.1186/s13020-021-00507-1
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Article ; Online: Short-Term Effects of Bamboo Biochar and Oyster Shell Powder on Soil Organic Carbon Fraction, Microbial Respiration, and Enzymatic Stoichiometry in a Lei Bamboo Plantation

Ji, Haonan / Yuan, Gensheng / Liu, Yang / Yu, Jinzhu / Li, Songhao / Wu, Qifeng / Qin, Hua / Chen, Junhui

Forests. 2023 Apr. 21, v. 14, no. 4

2023

Abstract: Both biochar and oyster shell powder have been known as promising amendments to ameliorate soil acidity and enhance soil fertility. However, it is still unclear how their application alone and in combination affect the soil organic carbon (C) fraction ... ...

Abstract	Both biochar and oyster shell powder have been known as promising amendments to ameliorate soil acidity and enhance soil fertility. However, it is still unclear how their application alone and in combination affect the soil organic carbon (C) fraction and microbial activity in subtropical bamboo plantations. Therefore, to investigate the effects of biochar and oyster shell powder on soil microbial respiration, organic C fractions, microbial biomass, and enzyme activities related to C, N and P cycling, topsoil samples were collected from plots in a bamboo (Phyllostachys praecox) plantation that has been amended with oyster shell powder at 4 t ha⁻¹ (T), bamboo biochar at 10 t ha⁻¹ (B), and their combination (TB, with 4 t ha⁻¹ T and 10 t ha⁻¹ B) for 8 months. Our results showed that T alone significantly increased soil microbial respiration by 21.5%, whereas B alone and TB significantly decreased soil microbial respiration and metabolic quotient compared with T. T alone also increased soil pH, the size of labile C pool and the activities of β−glucosidase and cellobiosidase, whereas TB rather than B increased soil pH, the recalcitrant C pool size and declined these enzyme activities relative to T. T alone significantly enhanced microbial C limitation by 28.6% and decreased P limitation by 13.0%, while TB decreased microbial C limitation and increased microbial C use efficiency (CUE). Structural equation modeling indicated that T enhanced soil microbial respiration through increasing soil pH and enzyme activity, while biochar co-addition weakened the stimulation of T on microbial respiration by increasing soil recalcitrant C pool size and microbial metabolic quotient. Our study suggests that adding bamboo biochar together with oyster shell powder could be a better strategy to decrease soil C loss and ameliorate soil acidity in bamboo plantations compared with the application of oyster shell powder alone.
Keywords	Phyllostachys violascens ; bamboos ; biochar ; carbon sinks ; enzyme activity ; enzymes ; equations ; microbial activity ; microbial biomass ; oyster shells ; soil fertility ; soil organic carbon ; soil pH ; stoichiometry ; topsoil
Language	English
Dates of publication	2023-0421
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ZDB-ID	2527081-3
ISSN	1999-4907
ISSN	1999-4907
DOI	10.3390/f14040853
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Response of carbon uptake to abiotic and biotic drivers in an intensively managed Lei bamboo forest.

Liu, Yuli / Zhou, Guomo / Du, Huaqiang / Berninger, Frank / Mao, Fangjie / Li, Xuejian / Chen, Liang / Cui, Lu / Li, Yangguang / Zhu, Di'en / Xu, Lin

Journal of environmental management

2018 Volume 223, Page(s) 713–722

Abstract: Lei bamboo (Phyllostachys praecox) is widely distributed in southeastern China. We used eddy ... covariance to analyze carbon sequestration capacity of a Lei bamboo forest (2011-2013) and to identify ...

Abstract	Lei bamboo (Phyllostachys praecox) is widely distributed in southeastern China. We used eddy covariance to analyze carbon sequestration capacity of a Lei bamboo forest (2011-2013) and to identify the seasonal biotic and abiotic determinants of carbon fluxes. A machine learning algorithm called random forest (RF) was used to identify factors that affected carbon fluxes. The RF model predicted well the gross ecosystem productivity (GEP), ecosystem respiration (RE) and net ecosystem exchange (NEE), and displayed variations in the drivers between different seasons. Mean annual NEE, RE, and GEP were -105.2 ± 23.1, 1264.5 ± 45.2, and 1369.6 ± 52.5 g C m
MeSH term(s)	Carbon ; Carbon Cycle ; Carbon Dioxide ; Carbon Sequestration ; China ; Ecosystem ; Models, Theoretical
Chemical Substances	Carbon Dioxide (142M471B3J) ; Carbon (7440-44-0)
Language	English
Publishing date	2018-07-03
Publishing country	England
Document type	Journal Article
ZDB-ID	184882-3
ISSN	1095-8630 ; 0301-4797
ISSN (online)	1095-8630
ISSN	0301-4797
DOI	10.1016/j.jenvman.2018.06.046
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Article: Application of Convolutional Neural Network on Lei Bamboo Above-Ground-Biomass (AGB) Estimation Using Worldview-2

Dong, Luofan / Du, Huaqiang / Han, Ning / Li, Xuejian / Zhu, Di’en / Mao, Fangjie / Zhang, Meng / Zheng, Junlong / Liu, Hua / Huang, Zihao / He, Shaobai

Remote Sensing. 2020 Mar. 16, v. 12, no. 6

2020

Abstract: Above-ground biomass (AGB) directly relates to the productivity of forests. Precisely, AGB mapping for regional forests based on very high resolution (VHR) imagery is widely needed for evaluation of productivity. However, the diversity of variables and ... ...

Abstract	Above-ground biomass (AGB) directly relates to the productivity of forests. Precisely, AGB mapping for regional forests based on very high resolution (VHR) imagery is widely needed for evaluation of productivity. However, the diversity of variables and algorithms and the difficulties inherent in high resolution optical imagery make it complex. In this paper, we explored the potentials of the state-of-art algorithm convolutional neural networks (CNNs), which are widely used for its high-level representation, but rarely applied for AGB estimation. Four experiments were carried out to compare the performance of CNNs and other state-of-art Machine Learning (ML) algorithms: (1) performance of CNN using bands, (2) performance of Random Forest (RF), support vector regression (SVR), artificial neural network (ANN) on bands, and vegetation indices (VIs). (3) Performance of RF, SVR, and ANN on gray-level co-occurrence matrices (GLCM), and exploratory spatial data analysis (ESDA), and (4) performance of RF, SVR, and ANN based on all combined data and ESDA+VIs. CNNs reached satisfactory results (with R² = 0.943) even with limited input variables (i.e., only bands). In comparison, RF and SVR with elaborately designed data obtained slightly better accuracy than CNN. For examples, RF based on GLCM textures reached an R² of 0.979 and RF based on all combined data reached a close R² of 0.974. However, the results of ANN were much worse (with the best R² of 0.885).
Keywords	aboveground biomass ; algorithms ; artificial intelligence ; bamboos ; forests ; neural networks ; regression analysis ; remote sensing ; spatial data ; vegetation index
Language	English
Dates of publication	2020-0316
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs12060958
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Application of Convolutional Neural Network on Lei Bamboo Above-Ground-Biomass (AGB) Estimation Using Worldview-2

Luofan Dong / Huaqiang Du / Ning Han / Xuejian Li / Di’en Zhu / Fangjie Mao / Meng Zhang / Junlong Zheng / Hua Liu / Zihao Huang / Shaobai He

Remote Sensing, Vol 12, Iss 6, p

2020 Volume 958

Abstract	Above-ground biomass (AGB) directly relates to the productivity of forests. Precisely, AGB mapping for regional forests based on very high resolution (VHR) imagery is widely needed for evaluation of productivity. However, the diversity of variables and algorithms and the difficulties inherent in high resolution optical imagery make it complex. In this paper, we explored the potentials of the state-of-art algorithm convolutional neural networks (CNNs), which are widely used for its high-level representation, but rarely applied for AGB estimation. Four experiments were carried out to compare the performance of CNNs and other state-of-art Machine Learning (ML) algorithms: (1) performance of CNN using bands, (2) performance of Random Forest (RF), support vector regression (SVR), artificial neural network (ANN) on bands, and vegetation indices (VIs). (3) Performance of RF, SVR, and ANN on gray-level co-occurrence matrices (GLCM), and exploratory spatial data analysis (ESDA), and (4) performance of RF, SVR, and ANN based on all combined data and ESDA+VIs. CNNs reached satisfactory results (with R 2 = 0.943) even with limited input variables (i.e., only bands). In comparison, RF and SVR with elaborately designed data obtained slightly better accuracy than CNN. For examples, RF based on GLCM textures reached an R 2 of 0.979 and RF based on all combined data reached a close R 2 of 0.974. However, the results of ANN were much worse (with the best R 2 of 0.885).
Keywords	deep learning (dl) ; machine learning (ml) ; above ground biomass (agb) ; very high-resolution imagery ; textures ; Science ; Q
Subject code	006 ; 333
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: A network pharmacology-based approach to explore the active ingredients and molecular mechanism of Lei-gong-gen formula granule on a spontaneously hypertensive rat model

Qiaofeng Li / Taijin Lan / Songhua He / Weiwei Chen / Xiaolan Li / Weiquan Zhang / Ying Liu / Qiuping Zhang / Xin Chen / Yaoyao Han / Zhiheng Su / Dan Zhu / Hongwei Guo

Chinese Medicine, Vol 16, Iss 1, Pp 1-

2021 Volume 21

Abstract: Abstract Background Lei-gong-gen formula granule (LFG) is a folk prescription derived from Zhuang ...

Abstract	Abstract Background Lei-gong-gen formula granule (LFG) is a folk prescription derived from Zhuang nationality, the largest ethnic minority among 56 nationalities in China. It consists of three herbs, namely Eclipta prostrata (L.) L., Smilax glabra Roxb, and Centella asiatica (L.) Urb. It has been widely used as health protection tea for hundreds of years to prevent hypertension in Guangxi Zhuang Autonomous Region. The purpose of this study is to validate the antihypertensive effect of LFG on the spontaneously hypertensive rat (SHR) model, and to further identify the effective components and anti-hypertension mechanism of LFG. Methods The effects of LFG on blood pressure, body weight, and heart rate were investigated in vivo using the SHR model. The levels of NO, ANG II, and ET-1 in the serum were measured, and pathological changes in the heart were examined by H&E staining. The main active components of LFG, their corresponding targets, and hypertension associated pathways were discerned through network pharmacology analysis based on the Traditional Chinese Medicine Systems Pharmacology (TCMSP), Traditional Chinese Medicine Integrated Database (TCMID), and the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM). Then the predicted results were further verified by molecular biology experiments such as RT-qPCR and western blot. Additionally, the potential active compounds were predicted by molecular docking technology, and the chemical constituents of LFG were analyzed and identified by UPLC-QTOF/MS technology. Finally, an in vitro assay was performed to investigate the protective effects of potential active compounds against hydrogen peroxide (H2O2) induced oxidative damage in human umbilical vein endothelial cells (HUVEC). Results LFG could effectively reduce blood pressure and increase serum NO content in SHR model. Histological results showed that LFG could ameliorate pathological changes such as cardiac hypertrophy and interstitial inflammation. From network ...
Keywords	Centella asiatica (L.) Urb ; Eclipta prostrata (L.) L ; Smilax glabra Roxb ; Hypertension ; Network pharmacology ; Other systems of medicine ; RZ201-999
Subject code	500
Language	English
Publishing date	2021-10-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Lei-Shi Li: a giant in international nephrology.

Liu, Zhi-Hong / Dworkin, Lance D / Atkins, Robert C

Kidney international

2010 Volume 77, Issue 12, Page(s) 1051–1052

MeSH term(s)	Biomedical Research/history ; China ; History, 20th Century ; History, 21st Century ; Nephrology/history
Language	English
Publishing date	2010-06
Publishing country	United States
Document type	Biography ; Historical Article ; Journal Article
ZDB-ID	120573-0
ISSN	1523-1755 ; 0085-2538
ISSN (online)	1523-1755
ISSN	0085-2538
DOI	10.1038/ki.2010.133
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Article: Response of carbon uptake to abiotic and biotic drivers in an intensively managed Lei bamboo forest

Liu, Yuli / Zhou, Guomo / Du, Huaqiang / Berninger, Frank / Mao, Fangjie / Li, Xuejian / Chen, Liang / Cui, Lu / Li, Yangguang / Zhu, Di'en / Xu, Lin

Journal of environmental management. 2018 Oct. 01, v. 223

2018

Abstract	Lei bamboo (Phyllostachys praecox) is widely distributed in southeastern China. We used eddy covariance to analyze carbon sequestration capacity of a Lei bamboo forest (2011–2013) and to identify the seasonal biotic and abiotic determinants of carbon fluxes. A machine learning algorithm called random forest (RF) was used to identify factors that affected carbon fluxes. The RF model predicted well the gross ecosystem productivity (GEP), ecosystem respiration (RE) and net ecosystem exchange (NEE), and displayed variations in the drivers between different seasons. Mean annual NEE, RE, and GEP were −105.2 ± 23.1, 1264.5 ± 45.2, and 1369.6 ± 52.5 g C m−2, respectively. Climate warming increased RE more than GEP when water inputs were not limiting. Summer drought played little role in suppressing GEP, but low soil moisture contents suppressed RE and increased the carbon sink during drought in the summer. The most important drivers of NEE were soil temperature in spring, summer, and winter, and photosynthetically active radiation in autumn. Air and soil temperature were important drivers of GEP in all seasons.
Keywords	Phyllostachys violascens ; air ; air temperature ; algorithms ; artificial intelligence ; autumn ; bamboos ; carbon ; carbon sequestration ; carbon sinks ; drought ; ecosystem respiration ; ecosystems ; eddy covariance ; forests ; global warming ; models ; net ecosystem exchange ; photosynthetically active radiation ; soil temperature ; spring ; summer ; winter ; China
Language	English
Dates of publication	2018-1001
Size	p. 713-722.
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	184882-3
ISSN	1095-8630 ; 0301-4797
ISSN (online)	1095-8630
ISSN	0301-4797
DOI	10.1016/j.jenvman.2018.06.046
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Comparing Simulated Carbon Budget of a Lei Bamboo Forest with Flux Tower Data

Xuehe Lu / Hong Jiang / Jinxun Liu / Cheng Sun / Ying Wang / Jiaxin Jin

Terrestrial, Atmospheric and Oceanic Sciences, Vol 25, Iss 3, p

2014 Volume 359

Abstract: ... Biosphere Simulator (IBIS) according the management of Lei bamboo forest. Some management, like ... compared model results with the observation data from a Lei bamboo flux tower. The simulated and observed ... results had achieved good consistency. Our simulated Lei bamboo forest yearly net ecosystem productivity ...

Abstract	Bamboo forest ecosystem is the part of the forest ecosystem. The distribution area of bamboo forest is limited, but in somewhere, like south China, it has been cultivate for a long time with human management. As the climate change has been take great effect on forest carbon budget, many researchers pay attention to the carbon budget in bamboo forest. Moreover cultivative management had a significant impact on the bamboo forest carbon budget. In this study, we modified a terrestrial ecosystem model named Integrated Biosphere Simulator (IBIS) according the management of Lei bamboo forest. Some management, like fertilization, shoots harvesting and organic mulching in winter, had been incorporated into model. Then we had compared model results with the observation data from a Lei bamboo flux tower. The simulated and observed results had achieved good consistency. Our simulated Lei bamboo forest yearly net ecosystem productivity (NEP) was 0.41 kgC a-1 of carbon, which is very close to the observation data 0.45 kgC a-1 of carbon. And the monthly simulated results can take the change of carbon budget in each month, similar to the data we got from flux tower. It reflects that the modified IBIS model can characterize the growth of bamboo forest and perform the simulation well. And then two groups of simulations were set to evaluate effects of cultivative managements on Lei bamboo forests carbon budget. And results showed that both fertilization and organic mulching had taken positive effects on Lei bamboo forests carbon sequestration.
Keywords	Lei bamboo forest ; Carbon budget ; Flux tower ; Ecological model ; Geography (General) ; G1-922 ; Geology ; QE1-996.5
Subject code	550
Language	English
Publishing date	2014-01-01T00:00:00Z
Publisher	Chinese Geoscience Union
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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