Deferoxamine regulates neuroinflammation and iron homeostasis in a mouse model of postoperative cognitive dysfunction

BACKGROUND: Postoperative cognitive dysfunction (POCD) is a common complication after surgery, especially amongst elderly patients. Neuroinflammation and iron homeostasis are key hallmarks of several neurological disorders. In this study, we investigated the role of deferoxamine (DFO), a clinically used iron chelator, in a mouse model of surgery-induced cognitive dysfunction and assessed its neuroprotective effects on neuroinflammation, oxidative stress, and memory function. METHODS: A model of laparotomy under general anesthesia and analgesia was used to study POCD. Twelve to 14 months C57BL/6J male mice were treated with DFO, and changes in iron signaling, microglia activity, oxidative stress, inflammatory cytokines, and neurotrophic factors were assessed in the hippocampus on postoperative days 3, 7, and 14. Memory function was evaluated using fear conditioning and Morris water maze tests. BV2 microglia cells were used to test the anti-inflammatory and neuroprotective effects of DFO. RESULTS: Peripheral surgical trauma triggered changes in hippocampal iron homeostasis including ferric iron deposition, increase in hepcidin and divalent metal transporter-1, reduction in ferroportin and ferritin, and oxidative stress. Microglia activation, inflammatory cytokines, brain-derived neurotropic factor impairments, and cognitive dysfunction were found up to day 14 after surgery. Treatment with DFO significantly reduced neuroinflammation and improved cognitive decline by modulating p38 MAPK signaling, reactive oxygen species, and pro-inflammatory cytokines release. CONCLUSIONS: Iron imbalance represents a novel mechanism underlying surgery-induced neuroinflammation and cognitive decline. DFO treatment regulates neuroinflammation and microglia activity after surgery

MyoPS A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images

Assessment of myocardial viability is essential in diagnosis and treatment management of patients suffering from myocardial infarction, and classification of pathology on myocardium is the key to this assessment. This work defines a new task of medical image analysis, i.e., to perform myocardial pathology segmentation (MyoPS) combining three-sequence cardiac magnetic resonance (CMR) images, which was first proposed in the MyoPS challenge, in conjunction with MICCAI 2020. The challenge provided 45 paired and pre-aligned CMR images, allowing algorithms to combine the complementary information from the three CMR sequences for pathology segmentation. In this article, we provide details of the challenge, survey the works from fifteen participants and interpret their methods according to five aspects, i.e., preprocessing, data augmentation, learning strategy, model architecture and post-processing. In addition, we analyze the results with respect to different factors, in order to examine the key obstacles and explore potential of solutions, as well as to provide a benchmark for future research. We conclude that while promising results have been reported, the research is still in the early stage, and more in-depth exploration is needed before a successful application to the clinics. Note that MyoPS data and evaluation tool continue to be publicly available upon registration via its homepage (www.sdspeople.fudan.edu.cn/zhuangxiahai/0/myops20/)

Integrated transcriptomics and metabolomics analysis provide insight into the resistance response of rice against brown planthopper

IntroductionThe brown planthopper (Nilaparvata lugens Stål, BPH) is one of the most economically significant pests of rice. The Bph30 gene has been successfully cloned and conferred rice with broad-spectrum resistance to BPH. However, the molecular mechanisms by which Bph30 enhances resistance to BPH remain poorly understood.MethodsHere, we conducted a transcriptomic and metabolomic analysis of Bph30-transgenic (BPH30T) and BPH-susceptible Nipponbare plants to elucidate the response of Bph30 to BPH infestation.ResultsTranscriptomic analyses revealed that the pathway of plant hormone signal transduction enriched exclusively in Nipponbare, and the greatest number of differentially expressed genes (DEGs) were involved in indole 3-acetic acid (IAA) signal transduction. Analysis of differentially accumulated metabolites (DAMs) revealed that DAMs involved in the amino acids and derivatives category were down-regulated in BPH30T plants following BPH feeding, and the great majority of DAMs in flavonoids category displayed the trend of increasing in BPH30T plants; the opposite pattern was observed in Nipponbare plants. Combined transcriptomics and metabolomics analysis revealed that the pathways of amino acids biosynthesis, plant hormone signal transduction, phenylpropanoid biosynthesis and flavonoid biosynthesis were enriched. The content of IAA significantly decreased in BPH30T plants following BPH feeding, and the content of IAA remained unchanged in Nipponbare. The exogenous application of IAA weakened the BPH resistance conferred by Bph30.DiscussionOur results indicated that Bph30 might coordinate the movement of primary and secondary metabolites and hormones in plants via the shikimate pathway to enhance the resistance of rice to BPH. Our results have important reference significance for the resistance mechanisms analysis and the efficient utilization of major BPH-resistance genes

Single-Cell RNA sequencing of leaf sheath cells reveals the mechanism of rice resistance to brown planthopper (Nilaparvata lugens)

The brown planthopper (BPH) (Nilaparvata lugens) sucks rice sap causing leaves to turn yellow and wither, often leading to reduced or zero yields. Rice co-evolved to resist damage by BPH. However, the molecular mechanisms, including the cells and tissues, involved in the resistance are still rarely reported. Single-cell sequencing technology allows us to analyze different cell types involved in BPH resistance. Here, using single-cell sequencing technology, we compared the response offered by the leaf sheaths of the susceptible (TN1) and resistant (YHY15) rice varieties to BPH (48 hours after infestation). We found that the 14,699 and 16,237 cells (identified via transcriptomics) in TN1 and YHY15 could be annotated using cell-specific marker genes into nine cell-type clusters. The two rice varieties showed significant differences in cell types (such as mestome sheath cells, guard cells, mesophyll cells, xylem cells, bulliform cells, and phloem cells) in the rice resistance mechanism to BPH. Further analysis revealed that although mesophyll, xylem, and phloem cells are involved in the BPH resistance response, the molecular mechanism used by each cell type is different. Mesophyll cell may regulate the expression of genes related to vanillin, capsaicin, and ROS production, phloem cell may regulate the cell wall extension related genes, and xylem cell may be involved in BPH resistance response by controlling the expression of chitin and pectin related genes. Thus, rice resistance to BPH is a complicated process involving multiple insect resistance factors. The results presented here will significantly promote the investigation of the molecular mechanisms underlying the resistance of rice to insects and accelerate the breeding of insect-resistant rice varieties

Real-Time and High-Resolution 3D Face Measurement via a Smart Active Optical Sensor

The 3D measuring range and accuracy in traditional active optical sensing, such as Fourier transform profilometry, are influenced by the zero frequency of the captured patterns. The phase-shifting technique is commonly applied to remove the zero component. However, this phase-shifting method must capture several fringe patterns with phase difference, thereby influencing the real-time performance. This study introduces a smart active optical sensor, in which a composite pattern is utilized. The composite pattern efficiently combines several phase-shifting fringes and carrier frequencies. The method can remove zero frequency by using only one pattern. Model face reconstruction and human face measurement were employed to study the validity and feasibility of this method. Results show no distinct decrease in the precision of the novel method unlike the traditional phase-shifting method. The texture mapping technique was utilized to reconstruct a nature-appearance 3D digital face

An Algorithm for Mining of Association Rules for the Information Communication Network Alarms Based on Swarm Intelligence

Due to the centralized management of information communication network, the network operator have to face these pressures, which come from the increasing network alarms and maintenance efficiency. The effective analysis on mining of the network alarm association rules is achieved by incorporating classic data association mining algorithm and swarm intelligence optimization algorithm. From the related concept of the information communication network, the paper analyzes the data characteristics and association logic of the network alarms. Besides, the alarm data are preprocessed and the main standardization information fields are screened. The APPSO algorithm is proposed on the basis of combining the evaluation method for support and confidence coefficient in the Apriori (AP) algorithm as well as the particle swarm optimization (PSO) algorithm. By establishing a sparse linked list, the algorithm is able to calculate the particle support thus further improving the performance of the APPSO algorithm. Based on the test for the network alarm data, it is discovered that rational setting of the particle swarm scale and number of iterations of the APPSO algorithm can be used to mine the vast majority and even all of the association rules and the mining efficiency is significantly improved, compared with Apriori algorithm

Impact of propofol versus sevoflurane anesthesia on molecular subtypes and immune checkpoints of glioma during surgery

Abstract Background Sevoflurane and propofol are two popular anesthetics used during glioblastoma (GBM) surgery. This investigation compared the molecular subtypes and immune checkpoints of cancer cells following GBM surgery under sevoflurane and propofol anesthesia. Method The expression profile data and clinical information of glioma samples of different grades were downloaded from The Cancer Genome Atlas database. Weighted gene coexpression network analysis was used to identify hub modules and key genes related to glioma grades (G2 and G3). The GEO database (GSE179004) was used to retrieve glioma surgical specimens with different anesthetic gene expression profiles. The differential expression of immune checkpoint genes under various anesthetic settings was examined using the R‐ggplot2. Results Compared to sevoflurane, propofol significantly downregulated SERPINI1 and CAMK2A expression. These are also important factors in glioma grading. Simultaneously, SERPINI1 and CAMK2A were also significantly related to the prognosis of GBM and lower‐grade glioma patients and acted as potential tumor suppressors. In addition, propofol increases the expression of the immune checkpoint molecule, PD‐L1. Conclusions Our study revealed that sevoflurane can more effectively prevent the development of glioma after surgery than propofol, and SERPINI1 can be used as a new independent prognostic factor for glioma

Monitoring Citrus Soil Moisture and Nutrients Using an IoT Based System

Chongqing mountain citrus orchard is one of the main origins of Chinese citrus. Its planting terrain is complex and soil parent material is diverse. Currently, the citrus fertilization, irrigation and other management processes still have great blindness. They usually use the same pattern and the same formula rather than considering the orchard terrain features, soil differences, species characteristics and the state of tree growth. With the help of the ZigBee technology, artificial intelligence and decision support technology, this paper has developed the research on the application technology of agricultural Internet of Things for real-time monitoring of citrus soil moisture and nutrients as well as the research on the integration of fertilization and irrigation decision support system. Some achievements were obtained including single-point multi-layer citrus soil temperature and humidity detection wireless sensor nodes and citrus precision fertilization and irrigation management decision support system. They were applied in citrus base in the Three Gorges Reservoir Area. The results showed that the system could help the grower to scientifically fertilize or irrigate, improve the precision operation level of citrus production, reduce the labor cost and reduce the pollution caused by chemical fertilizer

TMT-Based Proteomic Analysis Reveals the Molecular Mechanisms of Sodium Pheophorbide A against Black Spot Needle Blight Caused by <i>Pestalotiopsis neglecta</i> in <i>Pinus sylvestris</i> var. <i>mongolica</i>

Black spot needle blight is a minor disease in Mongolian Scots pine (Pinus sylvestris var. mongolica) caused by Pestalotiopsis neglecta, but it can cause economic losses in severe cases. Sodium pheophorbide a (SPA), an intermediate product of the chlorophyll metabolism pathway, is a compound with photoactivated antifungal activity, which has been previously shown to inhibit the growth of P. neglecta. In this study, SPA significantly reduced the incidence and disease index and enhanced the chlorophyll content and antioxidant enzyme activities of P. sylvestris var. mongolica. To further study the molecular mechanism of the inhibition, we conducted a comparative proteomic analysis of P. neglecta mycelia with and without SPA treatment. The cellular proteins were obtained from P. neglecta mycelial samples and subjected to a tandem mass tag (TMT)-labelling LC-MS/MS analysis. Based on the results of de novo transcriptome assembly, 613 differentially expressed proteins (DEPs) (p P. neglecta by SPA at the protein level and a theoretical basis for evaluating SPA as an antifungal agent to protect forests