Extreme rainfall and snowfall alter responses of soil respiration to nitrogen fertilization : a 3-year field experiment

Author Posting. © The Author(s), 2016. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Global Change Biology 23 (2017): 3403-3417, doi:10.1111/gcb.13620.Extreme precipitation is predicted to be more frequent and intense accompanying global warming, and may have profound impacts on soil respiration (Rs) and its components, i.e., autotrophic (Ra) and heterotrophic (Rh) respiration. However, how natural extreme rainfall or snowfall events affect these fluxes are still lacking, especially under nitrogen (N) fertilization. In this study, extreme rainfall and snowfall events occurred during a 3-year field experiment, allowing us to examine their effects on the response of Rs, Rh and Ra to N supply. In normal rainfall years of 2011/2012 and 2012/2013, N fertilization significantly stimulated Rs by 23.9% and 10.9%, respectively. This stimulation was mainly due to the increase of Ra because of N-induced increase in plant biomass. In the record wet year of 2013/2014, however, Rs was independent on N supply because of the inhibition effect of the extreme rainfall event. Compared with those in other years, Rh and Ra were reduced by 36.8% and 59.1%, respectively, which were likely related to the anoxic stress on soil microbes and decreased photosynthates supply. Although N supply did not affect annual Rh, the response ratio (RR) of Rh flux to N fertilization decreased firstly during growing season, increased in nongrowing season and peaked during spring thaw in each year. Nongrowing season Rs and Rh contributed 5.5–16.4% to their annual fluxes, and were higher in 2012/2013 than other years due to the extreme snowfall inducing higher soil moisture during spring thaw. The RR of nongrowing season Rs and Rh decreased in years with extreme snowfall or rainfall compared to those in normal years. Overall, our results highlight the significant effects of extreme precipitation on responses of Rs and its components to N fertilization, which should be incorporated into models to improve the prediction of carbon-climate feedbacks.This research was funded by the Chinese Academy of Sciences (XDB15020100) and the National Natural Science Foundation of China (31561143011).2017-12-2

Empirical analysis of current status data for additive hazards model with auxiliary covariates

summary:In practice, it often occurs that some covariates of interest are not measured because of various reasons, but there may exist some auxiliary information available. In this case, an issue of interest is how to make use of the available auxiliary information for statistical analysis. This paper discusses statistical inference problems in the context of current status data arising from an additive hazards model with auxiliary covariates. An empirical log-likelihood ratio statistic for the regression parameter vector is defined and its limiting distribution is shown to be a standard chi-squared distribution. A profile empirical log-likelihood ratio statistic for a sub-vector of the parameters and its asymptotic distribution are also studied. To assess the finite sample performance of the proposed methods, simulation studies are implemented and simulation results show that the methods work well

Corporate Social Responsibility Reporting, Pyramidal Structure And Political Interference: Evidence From China

This paper attempts to investigate the relation between pyramidal structure and corporate social responsibility (CSR) reporting quality and the effect of political interference on the relation. Based on 1388 Chinese A-share listed firms during 2010-2012, this paper demonstrates that the separation between control and ownership rights is significantly and positively related to the CSR reporting quality in the state-owned firms (SOFs), while negatively related to the CSR reporting quality in the non-state-owned firms (NSOFs). Results also indicate that the pyramidal layer between the bottom firms and their top ultimate owners is negatively related to CSR reporting quality, particularly significant for the NSOFs. Our research enriches the corporate governance literature by giving insights into the mechanism of pyramidal structure in corporate reporting, and extends the understanding of political interference in the CSR field. This study has public policy implications for China as well as a number of other countries in the Asia–Pacific region.

mTORC1 signalling and eIF4E/4E-BP1 translation initiation factor stoichiometry influence recombinant protein productivity from GS-CHOK1 cells

Many protein-based biotherapeutics are produced in cultured Chinese hamster ovary (CHO) cell lines. Recent reports have demonstrated that translation of recombinant mRNAs and global control of the translation machinery via mammalian target of rapamycin (mTOR) signalling are important determinants of the amount and quality of recombinant protein such cells can produce. mTOR complex 1 (mTORC1) is a master regulator of cell growth/division, ribosome biogenesis and protein synthesis, but the relationship between mTORC1 signalling, cell growth and proliferation and recombinant protein yields from mammalian cells, and whether this master regulating signalling pathway can be manipulated to enhance cell biomass and recombinant protein production (rPP) are not well explored. We have investigated mTORC1 signalling and activity throughout batch culture of a panel of sister recombinant glutamine synthetase-CHO cell lines expressing different amounts of a model monoclonal IgG4, to evaluate the links between mTORC1 signalling and cell proliferation, autophagy, recombinant protein expression, global protein synthesis and mRNA translation initiation. We find that the expression of the mTORC1 substrate 4E-binding protein 1 (4E-BP1) fluctuates throughout the course of cell culture and, as expected, that the 4E-BP1 phosphorylation profiles change across the culture. Importantly, we find that the eIF4E/4E-BP1 stoichiometry positively correlates with cell productivity. Furthermore, eIF4E amounts appear to be co-regulated with 4E-BP1 amounts. This may reflect a sensing of either change at the mRNA level as opposed to the protein level or the fact that the phosphorylation status, as well as the amount of 4E-BP1 present, is important in the co-regulation of eIF4E and 4E-BP1

Dynamics of soil microbial communities involved in carbon cycling along three successional forests in southern China

Dynamics of plant communities during forest succession have been received great attention in the past decades, yet information about soil microbial communities that are involved in carbon cycling remains limited. Here we investigated soil microbial community composition and carbohydrate degradation potential using metagenomic analysis and examined their influencing factors in three successional subtropical forests in southern China. Results showed that the abundances of soil bacteria and fungi increased (p ≤ 0.05 for both) with forest succession in relation to both soil and litter characteristics, whereas the bacterial diversity did not change (p \u3e 0.05) and the fungal diversity of Shannon-Wiener index even decreased (p ≤ 0.05). The abundances of microbial carbohydrate degradation functional genes of cellulase, hemicellulase, and pectinase also increased with forest succession (p ≤ 0.05 for all). However, the chitinase gene abundance did not change with forest succession (p \u3e 0.05) and the amylase gene abundance decreased firstly in middlesuccession forest and then increased in late-succession forest. Further analysis indicated that changes of functional gene abundance in cellulase, hemicellulase, and pectinase were primarily affected by soil organic carbon, soil total nitrogen, and soil moisture, whereas the variation of amylase gene abundance was well explained by soil phosphorus and litterfall. Overall, we created a metagenome profile of soil microbes in subtropical forest succession and fostered our understanding of microbially-mediated soil carbon cycling

BOAT: An Experimental Platform for Researchers to Comparatively and Reproducibly Evaluate Bug Localization Techniques

BOAT available at http://www.vlis.zju.edu.cn/blp.</p

Machine Learning Methods in Real-World Studies of Cardiovascular Disease

Objective: Cardiovascular disease (CVD) is one of the leading causes of death worldwide, and answers are urgently needed regarding many aspects, particularly risk identification and prognosis prediction. Real-world studies with large numbers of observations provide an important basis for CVD research but are constrained by high dimensionality, and missing or unstructured data. Machine learning (ML) methods, including a variety of supervised and unsupervised algorithms, are useful for data governance, and are effective for high dimensional data analysis and imputation in real-world studies. This article reviews the theory, strengths and limitations, and applications of several commonly used ML methods in the CVD field, to provide a reference for further application. Methods: This article introduces the origin, purpose, theory, advantages and limitations, and applications of multiple commonly used ML algorithms, including hierarchical and k-means clustering, principal component analysis, random forest, support vector machine, and neural networks. An example uses a random forest on the Systolic Blood Pressure Intervention Trial (SPRINT) data to demonstrate the process and main results of ML application in CVD. Conclusion: ML methods are effective tools for producing real-world evidence to support clinical decisions and meet clinical needs. This review explains the principles of multiple ML methods in plain language, to provide a reference for further application. Future research is warranted to develop accurate ensemble learning methods for wide application in the medical field

Targeting eIF4A Triggers an Interferon Response to Synergize With Chemotherapy and Suppress Triple-Negative Breast Cancer

Protein synthesis is frequently dysregulated in cancer and selective inhibition of mRNA translation represents an attractive cancer therapy. Here, we show that therapeutically targeting the RNA helicase eIF4A with zotatifin, the first-in-class eIF4A inhibitor, exerts pleiotropic effects on both tumor cells and the tumor immune microenvironment in a diverse cohort of syngeneic triple-negative breast cancer (TNBC) mouse models. Zotatifin not only suppresses tumor cell proliferation but also directly repolarizes macrophages toward an M1-like phenotype and inhibits neutrophil infiltration, which sensitizes tumors to immune checkpoint blockade. Mechanistic studies revealed that zotatifin reprograms the tumor translational landscape, inhibits the translation of Sox4 and Fgfr1, and induces an interferon (IFN) response uniformly across models. The induction of an IFN response is partially due to the inhibition of Sox4 translation by zotatifin. A similar induction of IFN-stimulated genes was observed in breast cancer patient biopsies following zotatifin treatment. Surprisingly, zotatifin significantly synergizes with carboplatin to trigger DNA damage and an even heightened IFN response, resulting in T cell-dependent tumor suppression. These studies identified a vulnerability of eIF4A in TNBC, potential pharmacodynamic biomarkers for zotatifin, and provide a rationale for new combination regimens consisting of zotatifin and chemotherapy or immunotherapy as treatments for TNBC

The Immune Landscape of Undifferentiated Pleomorphic Sarcoma

INTRODUCTION: Undifferentiated pleomorphic sarcoma (UPS) can be associated with a relatively dense immune infiltration. Immune checkpoint inhibitors (anti-PD1, anti-PDL1, and anti-CTLA4) are effective in 20% of UPS patients. We characterize the immune microenvironment of UPS and its association with oncologic outcomes. MATERIAL AND METHODS: Surgically resected UPS samples were stained by immunohistochemistry (IHC) for the following: tumor-associated immune cells (CD3, CD8, CD163, CD20), immune checkpoints (stimulatory: OX40, ICOS; inhibitory: PD-L1, LAG3, IDO1, PD1), and the adenosine pathway (CD73, CD39). Sections were reviewed for the presence of lymphoid aggregates (LA). Clinical data were retrospectively obtained for all samples. The Wilcoxon rank-sum and Kruskal-Wallis tests were used to compare distributions. Correlations between biomarkers were measured by Spearman correlation. Univariate and multivariate Cox models were used to identify biomarkers associated with overall survival (OS) and disease-free survival (DFS). Unsupervised clustering was performed, and Kaplan-Meier curves and log-rank tests used for comparison of OS and DFS between immune clusters. RESULTS: Samples analyzed (n=105) included 46 primary tumors, 34 local recurrences, and 25 metastases. LA were found in 23% (n=10/43), 17% (n=4/24), and 30% (n=7/23) of primary, recurrent, and metastatic samples, respectively. In primary UPS, CD73 expression was significantly higher after preoperative radiation therapy (p=0.009). CD39 expression was significantly correlated with PD1 expression (primary: p=0.002, recurrent: p=0.004, metastatic: p=0.001), PD-L1 expression (primary: p=0.009), and CD3+ cell densities (primary: p=0.016, recurrent: p=0.043, metastatic: p=0.028). In recurrent tumors, there was a strong correlation between CD39 and CD73 (p=0.015), and both were also correlated with CD163+ cell densities (CD39 p=0.013; CD73 p\u3c0.001). In multivariate analyses, higher densities of CD3+ and CD8+ cells (Cox Hazard Ratio [HR]=0.33; p=0.010) were independently associated with OS (CD3+, HR=0.19, p\u3c0.001; CD8+, HR= 0.33, p=0.010) and DFS (CD3+, HR=0.34, p=0.018; CD8+, HR=0.34, p= 0.014). Unsupervised clustering of IHC values revealed three immunologically distinct clusters: immune high, intermediate, and low. In primary tumors, these clusters were significantly associated with OS (log-rank p\u3c0.0001) and DFS (p\u3c0.001). CONCLUSION: We identified three immunologically distinct clusters of UPS Associated with OS and DFS. Our data support further investigations of combination anti-PD-1/PD-L1 and adenosine pathway inhibitors in UPS