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Lung ischemia–reperfusion injury is a common clinical concern. As the injury occurs, the pulmonary afferent nerves play a key role in regulating respiratory functions under pathophysiological conditions. The present study was to examine products of oxidative stress and expression of transient receptor potential A1 in the commissural nucleus of the solitary tract after lung ischemia–reperfusion injury; and further to determine molecular mediators linking to activation of oxidative stress and transient receptor potential ankyrin A1. A rat model of lung ischemia–reperfusion injury was used. Enzyme-linked immunosorbent assay and western blot analysis were employed to examine products of oxidative stress (i.e. 8-isoprostaglandin F2α and 8-hydroxy-2′-deoxyguanosine), and expression of transient receptor potential A1, Nrf2-antioxidant response element, and NADPH oxidase. 8-isoprostaglandin F2α and 8-hydroxy-2′-deoxyguanosine were amplified in the commissural nucleus of the solitary tract of lung ischemia–reperfusion injury rats, accompanied with downregulation of Nrf2-antioxidant response element, and upregulation of NOX4 and transient receptor potential A1. Blocking NADPH oxidase (subtype NOX4) decreased products of oxidative stress in the commissural nucleus of the solitary tract and attenuated upregulation of transient receptor potential A1 induced by lung ischemia–reperfusion injury. Our data revealed specific signaling pathways by which lung ischemia–reperfusion injury impairs Nrf2-antioxidant response and activates oxidative stress in the brainstem thereby leading to amplification of transient receptor potential A1 receptor likely via products of oxidative stress. Data suggest the abnormalities in the pulmonary afferent signals at the brainstem level which is likely to affect respiratory functions as lung ischemia–reperfusion injury occurs.

Abstract Background Effective noninvasive biomarkers of gastric cancer (GC) are critical for early detection and improvement of prognosis. We performed genome‐wide long non‐coding RNA (lncRNA) microarray analysis to identify and validate novel GC biomarkers depending on a high‐risk population cohort. Methods LncRNA profiles were described using the Human LncRNA Microarray between GC and control plasma samples. The differential candidate lncRNAs were validated in two stages by quantitative reverse transcription polymerase chain reaction (qRT‐PCR). We further evaluated the joint effect between the GC‐associated lncRNA and Helicobacter pylori (H. pylori) infection on the risk of cardia and non‐cardia GC, respectively. Results Different lncRNA expression profiles were identified between GC and control plasma with a total of 1206 differential lncRNAs including 470 upregulated and 736 downregulated in GC compared with the control group. The eight significantly upregulated lncRNAs (RP11‐521D12.1, AC011995.3, RP11‐5P4.3, RP11‐244 K5.6, RP11‐422 J15.1, CTD‐2306 M5.1, CTC‐428G20.2, and AC009133.20) in GC cases both in the present study and a similar microarray screening study by our collaborative team were selected for a two‐stage validation. After the large sample size validation, the subjects with higher expression of RP11‐244 K5.6 showed a significantly increased risk of GC with an adjusted odds ratio (OR) as 2.68 and 95% confidence interval (CI) as 1.15–6.24. Joint effects between RP11‐244 K5.6 expression and H. pylori infection on the risk of GC were evaluated with no statistical significance. Conclusions Our study found different lncRNA expression profiles between GC and control plasma and preliminarily identified RP11‐244 K5.6 as a potential noninvasive biomarker for GC screening.

Abstract Fine‐grained classification is a challenging task due to the difficulty of finding discriminative features and the localization of feature regions. To handle these challenges, a novel visual classification framework on panoramic attention mechanism that combines multiple attention networks to locate and identify features with more semantic interest is proposed. Firstly, based on the classical convolutional neural network, the global information of the image feature is expressed by linear fusion. Secondly, the foreground attention branch is used to further extract the distinguishing details of the salient features. Then, more features are mined from the complementary object area through the background attention branch to learn more perfect fine‐grained feature expression. Finally, three network branches are trained together to enhance the network's ability to express representative features of fine‐grained images. Our model can be viewed as a multi‐branch network, which benefits each other and optimizes the network together. Experiments were conducted on CUB‐200‐2011, Stanford Dogs and FGVC‐Aircraft datasets, and the accuracy was used as the quantitative measurement. Experimental results show that the proposed method has the highest accuracy; the average accuracy is 89.8%. It is effective and superior to the current advanced methods.

Abstract Streamflow sensitivity to climate change is an important indicator for evaluating the effects of climate change on terrestrial water. This study analyzed the spatial pattern and seasonality of streamflow sensitivity to climate change for 425 catchments across China. The results indicate that precipitation is consistently a more important contributor than temperature to streamflow variability (mean streamflow sensitivity to annual precipitation [εP,a] = 0.92; absolute mean sensitivity to annual temperature [εT,a] = 0.05). Meanwhile, the seasonal sensitivity evaluation found that streamflow response to precipitation change in warm seasons (mean εP,w = 0.90) is significantly greater than in cool seasons (mean εP,c = 0.46), but the sensitivity of streamflow to changes in temperature was stronger in cool seasons than in warm seasons. The magnitude of streamflow sensitivity to temperature in cool seasons is significantly affected by elevation (Pearson's r = 0.31, P

Background Annexin 1 (ANXA1) expression is associated with the malignant tumor phenotype, making it an attractive therapeutic target. However, little is known about the regulation of ANXA1 in non‐small cell lung cancer (NSCLC). Methods We investigated the biological roles of ANXA1 in tumor growth, migration, and invasion, and explored the possibility of ANXA1 as a potential therapeutic target for the treatment of NSCLC. Results Our findings revealed that ANXA1 enhanced nuclear factor (NF)‐κB activation in NSCLC cells by interaction with inhibitor of NF‐κB kinase complex subunit, IKKγ. We also found that NF‐κB could negatively regulate microRNA (miR)‐26a, and miR‐26a was regulated through the ANXA1–NF‐κB regulatory pathway. NF‐κB activation negatively regulated by miR‐26a was confirmed in NSCLC. Conclusion Together, these results provide evidence of the mechanisms of the ANXA1–NF‐κB–miR‐26a regulatory pathway in the invasion and migration in NSCLC.