Biological N fixation but not mineral N fertilization enhances the accumulation of N in peanut soil in maize/peanut intercropping system

Legume/cereal intercropping has the potential to maximize the use of resources to raise yields due to enhanced nitrogen (N) fixation by legume root nodules, while high N fertilization may inhibit the nodulation of legume. However, whether legume/cereal intercropping can promote the accumulation of soil N storage with N fertilization and its underlying mechanism are less clear. Here, we evaluated the long-term (5 years) effects of maize/peanut intercropping and mineral N fertilization on peanut soil total N content and soil N cycling functional genes. The experiment includes two planting patterns (peanut maize intercropping and peanut monocropping) with three N fertilization rates (0, 150, and 300 kg N ha−1). Intercropping increased soil total N content (STN) by average 18.2%, and the positive effect of intercropping on STN decreased with N application rate. Highest N application decreased the nodule fresh weight (NFW) by 64.3% and 46.0% in intercropping and monocropping system, respectively. However, intercropping has no effect on NFW. Intercropping increased the nifH gene abundance by average 26.5%. SEM analysis indicated that NFW and nifH gene abundance combined can explain 46% of the variance of STN. Our results indicate that biological N fixation but not mineral N fertilization enhances the accumulation of N in soil planted with peanut in maize/peanut intercropping system.info:eu-repo/semantics/publishedVersio

Faktor-Faktor Yang Mempengaruhi Pengungkapan Tanggung Jawab Sosial

Penelitian ini bertujuan untuk menentukan faktor-faktor yang mempengaruhi luasnya tingkat pengungkapan tanggung jawab sosial Perusahaan (Corporate Social Responsibility) dengan menguji pengaruh ukuran Perusahaan, profitabilitas, leverage, kepemilikan insti­tusional, ukuran dewan komisaris, ukuran dewan direksi, dan ukuran komite audit. Sampel yang digunakan adalah Perusahaan sektor pertambangan terdaftar di Bursa Efek Indonesia selama 2010-2012. Data diperoleh dari laporan keuangan auditan dan laporan tahunan serta laporan keberlanjutan (sustainability report) jika ada. Penelitian ini menggunakan pendekatan kuantitatif dengan analisis regresi linear berganda. Penelitian ini menunjukkan bahwa ukuran Perusahaan dan komite audit memiliki pengaruh positif terhadap peng­ungkapan tanggung jawab sosial. Tidak ditemukan bukti pengaruh profitabilitas, leverage, kepemilikan institusional, ukuran dewan komisaris, dan ukuran dewan direksi terhadap terhadap pengungkapan tanggung jawab sosial

The Last April

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Novel Genetic Risk and Metabolic Signatures of Insulin Signaling and Androgenesis in the Anovulation of Polycystic Ovary Syndrome

Funding Information: The authors are grateful to all staff in the PCOSAct group for their effort in the collection of blood samples and clinical dataset which used in current study. Special thanks to Prof. Attila Toth from Institute of Physiological Chemistry, Dresden, Germany for the REC114 antibody. This study was supported by the National key Research and Development Program of China (2019YFC1709500); the National Collaboration Project of Critical Illness by Integrating Chinese Medicine and Western Medicine; the Project of Heilongjiang Province Innovation Team “TouYan;” the Yi-Xun Liu and Xiao-Ke Wu Academician Workstation; the Innovation Team of Reproductive Technique with Integrative Chinese Medicine and Western Medicine in Xuzhou City, China; Heilongjiang University of Chinese Medicine from the National Clinical Trial Base; Heilongjiang Provincial Clinical Research Center for Ovary Diseases; the Research Grant Council (T13-602/21-N, C5045-20EF, and 14122021); and Food and Health Bureau in Hong Kong, China (06171026). Ben Willem J. Mol is supported by a National Health and Medical Research Council (NHMRC) Investigator grant (GNT1176437). Ben Willem J. Mol reports consultancy for ObsEva and Merck and travel support from Merck. Xiaoke Wu, Yongyong Shi, and Chi Chiu Wang developed the research question and designed the study. Xiaoke Wu, Yongyong Shi, Yijuan Cao, and Chi Chiu Wang designed the analysis. Yongyong Shi and Zhiqiang Li contributed to the design of the experiment of whole-exome plus targeted SNP sequencing and the analysis, and interpreted the results. Jingshu Gao, Hui Chang, Duojia Zhang, Jing Cong, Yu Wang, Qi Wu, Xiaoxiao Han, Pui Wah Jacqueline Chung, Yiran Li, and Lin Zeng contributed to the experiment of metabolic profile and immunofluorescent staining and the analysis, and interpreted the results. Astrid Borchert and Hartmut Kuhn provided antibody support and advice. Xu Zheng and Lingxi Chen contributed to create the predictive model with deep machine learning. Jian Li, Qi Wu, Hongli Ma, Xu Zheng, and Lingxi Chen contributed to the analysis of the clinical characteristics and interpreted the results. Jian Li, Hongli Ma, Hui Chang, Jing Cong, and Chi Chiu Wang drafted the manuscript. All authors reviewed and revised the manuscript. Xiaoke Wu is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Xiaoke Wu, Chi Chiu Wang, Yijuan Cao, Jian Li, Zhiqiang Li, Hongli Ma, Jingshu Gao, Hui Chang, Duojia Zhang, Jing Cong, Yu Wang, Qi Wu, Xiaoxiao Han, Pui Wah Jacqueline Chung, Yiran Li, Xu Zheng, Lingxi Chen, Lin Zeng, Astrid Borchert, Hartmut Kuhn, Zijiang Chen, Ernest Hung Yu Ng, Elisabet Stener-Victorin, Heping Zhang, Richard S. Legro, Ben Willem J. Mol, and Yongyong Shi declare that they have no conflict of interest or financial conflicts to disclose. Funding Information: This study was supported by the National key Research and Development Program of China ( 2019YFC1709500 ); the National Collaboration Project of Critical Illness by Integrating Chinese Medicine and Western Medicine ; the Project of Heilongjiang Province Innovation Team “TouYan;” the Yi-Xun Liu and Xiao-Ke Wu Academician Workstation; the Innovation Team of Reproductive Technique with Integrative Chinese Medicine and Western Medicine in Xuzhou City , China; Heilongjiang University of Chinese Medicine from the National Clinical Trial Base ; Heilongjiang Provincial Clinical Research Center for Ovary Diseases ; the Research Grant Council ( T13-602/21-N , C5045-20EF , and 14122021 ); and Food and Health Bureau in Hong Kong, China ( 06171026 ). Publisher Copyright: © 2023Peer reviewedPublisher PD

Exogenous Calcium Alleviates Oxidative Stress Caused by Salt Stress in Peanut Seedling Roots by Regulating the Antioxidant Enzyme System and Flavonoid Biosynthesis

Soil salinity is one of the adversity stresses plants face, and antioxidant defense mechanisms play an essential role in plant resistance. We investigated the effects of exogenous calcium on the antioxidant defense system in peanut seedling roots that are under salt stress by using indices including the transcriptome and absolute quantitative metabolome of flavonoids. Under salt stress conditions, the antioxidant defense capacity of enzymatic systems was weakened and the antioxidant capacity of the linked AsA-GSH cycle was effectively inhibited. In contrast, the ascorbate biosynthesis pathway and its upstream glycolysis metabolism pathway became active, which stimulated shikimate biosynthesis and the downstream phenylpropanoid metabolism pathway, resulting in an increased accumulation of flavonoids, which, as one of the antioxidants in the non-enzymatic system, provide hydroxyl radicals to scavenge the excess reactive oxygen species and maintain the plant’s vital activities. However, the addition of exogenous calcium caused changes in the antioxidant defense system in the peanut root system. The activity of antioxidant enzymes and the antioxidant capacity of the AsA-GSH cycle were enhanced. Therefore, glycolysis and phenylpropanoid metabolism do not exert antioxidant function, and flavonoids were no longer synthesized. In addition, antioxidant enzymes and the AsA-GSH cycle showed a trade-off relationship with sugars and flavonoids

Experimental Investigation of the Adsorption Characteristics of Mixed Coal and Variations of Specific Surface Areas before and after CH₄ Adsorption

Tectonic coal is a kind of soft coal that is generated during tectonic movement. Gas outbursts usually occur in seams containing both virgin coal and tectonic coal. To reveal the adsorption characteristics of this type of coal seam (containing both virgin coal and tectonic coal), both tectonic coal and virgin coal were collected from the same longwall face and a series of laboratory tests were conducted, including coal sorption tests and pore specific surface measurements. Both the tectonic coal and virgin coal were crushed into coal powder (0.18&#8315;0.25 mm) for the coal sorption tests. In these laboratory tests, different mass ratios between tectonic coal and virgin coal were tested. We found that with the increase of the percentage of tectonic coal, the adsorption volume showed a rising trend, reached its maximum value, and then decreased. The specific surface areas of the mixed coal samples had the same evolution trends as those of the adsorption volume. From the laboratory tests, we found that when the mass ratio of virgin coal to tectonic coal was 1:1, both the adsorption volume and the specific surface areas reached their maximum values. Due to the percentage variation of the tectonic coal in the panel with the advancement of the longwall face, when the tectonic coal accounted for 50% of the total coal, the gas content would rise. Thus, proper measures should be adopted for outburst hazards control. The mathematical model between the change of specific surface area and the stress and strain of pore expansion before and after gas adsorption was established, and the relationship between the change of pore structure and gas emission before and after gas adsorption was obtained. It provides a theoretical basis for further research on coal and gas outburst mechanisms

Experimental investigation of the adsorption characteristics of mixed coal and variations of specific surface areas before and after CH4 adsorption

Tectonic coal is a kind of soft coal that is generated during tectonic movement. Gas outbursts usually occur in seams containing both virgin coal and tectonic coal. To reveal the adsorption characteristics of this type of coal seam (containing both virgin coal and tectonic coal), both tectonic coal and virgin coal were collected from the same longwall face and a series of laboratory tests were conducted, including coal sorption tests and pore specific surface measurements. Both the tectonic coal and virgin coal were crushed into coal powder (0.18-0.25 mm) for the coal sorption tests. In these laboratory tests, different mass ratios between tectonic coal and virgin coal were tested. We found that with the increase of the percentage of tectonic coal, the adsorption volume showed a rising trend, reached its maximum value, and then decreased. The specific surface areas of the mixed coal samples had the same evolution trends as those of the adsorption volume. From the laboratory tests, we found that when the mass ratio of virgin coal to tectonic coal was 1:1, both the adsorption volume and the specific surface areas reached their maximum values. Due to the percentage variation of the tectonic coal in the panel with the advancement of the longwall face, when the tectonic coal accounted for 50% of the total coal, the gas content would rise. Thus, proper measures should be adopted for outburst hazards control. The mathematical model between the change of specific surface area and the stress and strain of pore expansion before and after gas adsorption was established, and the relationship between the change of pore structure and gas emission before and after gas adsorption was obtained. It provides a theoretical basis for further research on coal and gas outburst mechanisms

SNP set association analysis for genome-wide association studies.

Genome-wide association study (GWAS) is a promising approach for identifying common genetic variants of the diseases on the basis of millions of single nucleotide polymorphisms (SNPs). In order to avoid low power caused by overmuch correction for multiple comparisons in single locus association study, some methods have been proposed by grouping SNPs together into a SNP set based on genomic features, then testing the joint effect of the SNP set. We compare the performances of principal component analysis (PCA), supervised principal component analysis (SPCA), kernel principal component analysis (KPCA), and sliced inverse regression (SIR). Simulated SNP sets are generated under scenarios of 0, 1 and ≥ 2 causal SNPs model. Our simulation results show that all of these methods can control the type I error at the nominal significance level. SPCA is always more powerful than the other methods at different settings of linkage disequilibrium structures and minor allele frequency of the simulated datasets. We also apply these four methods to a real GWAS of non-small cell lung cancer (NSCLC) in Han Chinese population