Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983–2012, we find that topsoil (0–50 cm) volumetric water content during the growing season has declined significantly (p < 0.01), with a trend of −0.011 to −0.015 m3 m−3 per decade. Observed discharge declines for the three large river basins are consistent with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system.
Protein–protein interactions (PPIs) are essential for most living organisms’ process. Thus, detecting PPIs is extremely important to understand the molecular mechanisms of biological systems. Although many PPIs data have been generated by high-throughput technologies for a variety of organisms, the whole interatom is still far from complete. In addition, the high-throughput technologies for detecting PPIs has some unavoidable defects, including time consumption, high cost, and high error rate. In recent years, with the development of machine learning, computational methods have been broadly used to predict PPIs, and can achieve good prediction rate. In this paper, we present here PCVMZM, a computational method based on a Probabilistic Classification Vector Machines (PCVM) model and Zernike moments (ZM) descriptor for predicting the PPIs from protein amino acids sequences. Specifically, a Zernike moments (ZM) descriptor is used to extract protein evolutionary information from Position-Specific Scoring Matrix (PSSM) generated by Position-Specific Iterated Basic Local Alignment Search Tool (PSI-BLAST). Then, PCVM classifier is used to infer the interactions among protein. When performed on PPIs datasets of Yeast and H. Pylori, the proposed method can achieve the average prediction accuracy of 94.48% and 91.25%, respectively. In order to further evaluate the performance of the proposed method, the state-of-the-art support vector machines (SVM) classifier is used and compares with the PCVM model. Experimental results on the Yeast dataset show that the performance of PCVM classifier is better than that of SVM classifier. The experimental results indicate that our proposed method is robust, powerful and feasible, which can be used as a helpful tool for proteomics research.
The non-structural protein 1 (NS1) of different influenza A virus (IAV) strains can differentially regulate the activity of c-Jun terminal kinase (JNK) and PI-3 kinase (PI3K). Whether varying JNK and PI3K activation impacts autophagy and IAV replication differently remains uncertain. Here we report that H5N1 (A/mallard/Huadong/S/2005) influenza A virus induced functional autophagy, as evidenced by increased LC3 lipidation and decreased p62 levels, and the presence of autolysosomes in chicken fibroblast cells. H9N2 (A/chicken/Shanghai/F/98) virus weakly induced autophagy, whereas H1N1 virus (A/PR/8/34, PR8) blocked autophagic flux. H5N1 virus activated JNK but inhibited the PI-3 kinase pathway. In contrast, N9N2 virus infection led to modest JNK activation and strong PI-3 kinase activation; whereas H1N1 virus activated the PI-3 kinase pathway but did not activate JNK. SP600125, a JNK inhibitor, inhibited H5N1 virus-induced autophagy and virus replication in a DF-1 chicken fibroblast cell line. Our study uncovered a previously unrecognized role of JNK in IAV replication and autophagy.
Grammatical aspect captures ways in which a language uses grammatical markers to describe the temporal structure of an event. An event-related potential experiment was conducted to investigate event-related potential correlates of agreement violations of Chinese grammatical aspect. Participants read sentences containing either aspect agreement violations, semantic violations, or no violations. Semantic violations elicited an N400, whereas aspectual violations elicited a 200-400 ms posterior and left central negativity, followed by a P600, instead of left anterior negativity or N400, suggesting that left anterior negativities may not reflect a general, rule-governed, syntactically compositional process, and that grammatical aspect processing is at least not completely semantically driven. The negativity mostly reflects a failure to bind aspect markers or the detection of aspectual errors.
The prognostic value of the prognostic staging system that incorporated estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor‐2 (Her‐2), and histological grade has been validated in breast cancer (BC) patients, but the staging system seems to be somewhat complex. Recently, an updated bioscore system based on these tumor biological factors was proposed. The purpose of this study was to compare the prognostic stratification between prognostic staging system of American Joint Commission on Cancer (AJCC) and a simplified staging system based on the bioscore system and anatomic TNM staging for BC patients. A total of 44 593 patients with invasive ductal carcinoma who underwent radical resection between 2010 and 2011 were reviewed using the SEER database. The patients were reclassified into different groups according to the anatomic staging system, prognostic staging system, risk bioscore system, and simplified staging system, respectively. The prognostic differences between different groups were compared and clinicopathologic features were analyzed. The anatomic TNM staging failed to clearly distinguish the prognostic difference between stage IIIB and stage IIIC. Therefore, we proposed an adjusted anatomic staging, in which T1N3 and T2N3 were downstaged from stage IIIC to stage IIIB, and T4N2 was upstaged from stage IIIB to stage IIIC. Histological grade III, ER(−), PR(−), and Her‐2(−) were identified as independent prognostic factors in the multivariate analysis, and these factors were separately marked as 1 point. There were significant survival differences among different risk points except for the comparison between 0 and 1 point. The higher the risk points, the poorer the prognosis of BC patients. In addition, the curve distance between stage IIA and stage IIB was not significantly broaden according to the prognostic staging system. However, the prognostic stratification for BC patients could be significantly improved by the simplified staging system incorporated the bioscore system and adjusted anatomic staging. Several drawbacks may still exist in the prognostic staging system of AJCC. A simplified staging system that incorporated risk score system and the anatomic staging could provide more accurate prognostic information for BC patients.
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