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Chest X-ray is a radiological clinical assessment tool that has been commonly used to detect different types of lung diseases, such as lung tumors. In this paper, we use the Segmentation-based Deep Fusion Networks and Squeeze and Excitation blocks for model training. The proposed approach uses both wholes and cropped lung X-ray images and adds an attention mechanism to address the problems encountered during lesion identification, such as image misalignments, possible false positives from irrelevant objects, and the loss of small objects after image resizing. Two CNNs are used for feature extraction, and the extracted features are stitched together to form the final output, which is used to determine the presence of lung tumors in the image. Unlike previous methods which identify lesion heatmaps from X-ray images, we use the Semantic Segmentation via Gradient-Weighted Class Activation Mapping (Seg-Grad-CAM) to add semantic data for improved lung tumor localization. Experimental results show that our method achieves 98.51% accuracy and 99.01% sensitivity for classifying chest X-ray images with and without lung tumors. Furthermore, we combine the Seg-Grad-CAM and semantic segmentation for feature visualization. Experimental results show that the proposed approach achieves better results than previous methods that use weakly supervised learning for localization. The method proposed in this paper reduces the errors caused by subjective differences among radiologists, improves the efficiency of image interpretation and facilitates the making of correct treatment decisions.

Septic cardiomyopathy is characterized by impaired contractive function with mitochondrial dysregulation. Songorine is a typical active C20-diterpene alkaloid from the lateral root of Aconitum carmichaelii, which has been used for the treatment of heart failure. This study investigated the protective role of songorine in septic heart injury from the aspect of mitochondrial biogenesis. Songorine (10, 50 mg/kg) protected cardiac contractive function against endotoxin insult in mice with Nrf2 induction. In cardiomyocytes, lipopolysaccharide (LPS) evoked mitochondrial reactive oxygen species (ROS) production and redistributed STIM1 to interact with Orai1 for the formation of calcium release-activated calcium (CRAC) channels, mediating calcium influx, which were prevented by songorine, likely due to ROS suppression. Songorine activated Nrf2 by promoting Keap1 degradation, having a contribution to enhancing antioxidant defenses. When LPS shifted metabolism away from mitochondrial oxidative phosphorylation (OXPHOS) in cardiomyocytes, songorine upregulated mitochondrial genes involved in fatty acid β-oxidation, tricarboxylic acid (TCA) cycle and electron transport chain in a manner dependent on Nrf2, resultantly protecting the capability of OXPHOS. Songorine increased luciferase report gene activities of nuclear respiratory factor-1 (Nrf1) and mitochondrial transcription factor A (Tfam) dependently on Nrf2, indicative of the regulation of Nrf2/ARE and NRF1 signaling cascades. Songorine promoted PGC-1α binding to Nrf2, and the cooperation was required for songorine to activate Nrf2/ARE and NRF1 for the control of mitochondrial quality and quantity. In support, the beneficial effects of songorine on cardioprotection and mitochondrial biogenesis were diminished by cardiac Nrf2 deficiency in mice subjected to LPS challenge. Taken together, these results showed that Nrf2 transcriptionally promoted mitochondrial biogenesis in cooperation with PGC-1α. Songorine activated Nrf2/ARE and NRF1 signaling cascades to rescue cardiomyocytes from endotoxin insult, suggesting that protection of mitochondrial biogenesis was a way for pharmacological intervention to prevent septic heart injury.

The imbalance of energy consumption in wireless sensor networks (WSNs) may affect both network lifetime and reliability. Traditionally, the low-energy adaptive clustering hierarchy (LEACH) protocol has been applied to lower the energy consumption. Although the LEACH protocol can choose cluster heads (CHs) randomly to prevent a number of nodes from premature failure due to overutilization, the discrepancy in the energy distribution under different network topologies may result in a low network performance efficiency. In this paper, the LEACHenergy betweenness (LEACH-EB) model is proposed by taking energy consumption as a constraint condition. It can judge the equilibrium of clustering based on the energy betweenness of each node and realize the optimization of clustering in WSNs. The simulation results verify that the proposed LEACH-EB model can make the clustering more energy-efficient for better performance in terms of reliability and stability than the LEACH protocol. Additionally, the model can significantly reduce the extra energy loss caused by uneven clustering and thus prevent the degradation of network performance from the premature senescence of some nodes. [ABSTRACT FROM AUTHOR]

Effects of continuous cropping on rhizosphere soil physical and chemical properties, soil microbial activity, and community characteristics of Codonopsis pilosula were investigated. The C. pilosula plot(CK) fallow for five years and C. pilosula fields with different years of continuous cropping were studied using Illumina high-throughput sequencing technology combined with soil physical and chemical properties analysis. The response of rhizosphere soil physical and chemical properties, microbial activities, and microbial community characteristics to continuous cropping years of C. pilosula were investigated. The results were as follows:the contents of organic carbon, total phosphorus, total nitrogen, and salt in rhizosphere soil of C. pilosula increased with the extension of continuous cropping years. However, soil pH value decreased with the extension of continuous cropping years. Compared with that in the CK treatment, rhizosphere soil organic carbon content of C. pilosula in continuous cropping for one, two, three, and four years increased by 11.1%, 80.5%, 74.9%, and 78.2%, respectively. Total phosphorus content increased by 11.8%, 52.9%, 66.7%, and 78.4%, and total nitrogen content increased by 31.3%, 68.8%, 52.1%, and 56.3%, respectively. Soil salt content increased significantly under continuous cropping of three and four years, and soil conductivity increased by 54.2% and 84.7% compared with that in the CK treatment, respectively. The C/N ratio of microbial biomass in rhizosphere soil exhibited an increasing trend with the extension of continuous cropping years. Soil respiration entropy and microbial entropy showed a decreasing trend. With the increase in continuous cropping years, the diversity and abundance of bacteria in soil decreased, whereas the diversity and abundance of fungi increased. In addition, with the increase in continuous cropping years, the antagonistic effect between bacterial communities was enhanced, whereas the synergistic effect between fungal communities was mainly observed. Correlation analysis showed that soil total phosphorus, available potassium, carbon to nitrogen ratio of microbial biomass, soil respiration entropy, microbial biomass carbon, and electrical conductivity were the main factors affecting the changes in soil bacterial community characteristics. Soil total nitrogen, available potassium, available phosphorus, and soil respiration entropy were the main factors affecting the changes in fungal community characteristics. In conclusion, continuous cropping significantly changed the physical and chemical properties of soil and microbial activity and affected the abundance and diversity of bacteria and fungi in soil. This changed the interaction between microorganisms, which disrupted the stability of microbial communities in the soil.