Tetramethylpyrazine Nitrone Promotes the Clearance of Alpha-Synuclein via Nrf2-Mediated Ubiquitin-Proteasome System Activation.

Aggregation of α-synuclein (α-syn) and α-syn cytotoxicity are hallmarks of sporadic and familial Parkinson's disease (PD). Nuclear factor (erythroid-derived 2)-like 2 (Nrf2)-dependent enhancement of the expression of the 20S proteasome core particles (20S CPs) and regulatory particles (RPs) increases proteasome activity, which can promote α-syn clearance in PD. Activation of peroxisome proliferator-activated receptor γ co-activator 1α (PGC-1α) may reduce oxidative stress by strongly inducing Nrf2 gene expression. In the present study, tetramethylpyrazine nitrone (TBN), a potent-free radical scavenger, promoted α-syn clearance by the ubiquitin-proteasome system (UPS) in cell models overexpressing the human A53T mutant α-syn. In the α-syn transgenic mice model, TBN improved motor impairment, decreased the products of oxidative damage, and down-regulated the α-syn level in the serum. TBN consistently up-regulated PGC-1α and Nrf2 expression in tested models of PD. Additionally, TBN similarly enhanced the proteasome 20S subunit beta 8 (Psmb8) expression, which is linked to chymotrypsin-like proteasome activity. Furthermore, TBN increased the mRNA levels of both the 11S RPs subunits Pa28αß and a proteasome chaperone, known as the proteasome maturation protein (Pomp). Interestingly, specific siRNA targeting of Nrf2 blocked TBN's effects on Psmb8, Pa28αß, Pomp expression, and α-syn clearance. In conclusion, TBN promotes the clearance of α-syn via Nrf2-mediated UPS activation, and it may serve as a potentially disease-modifying therapeutic agent for PD.

Tetramethylpyrazine Nitrone alleviates D-galactose-induced murine skeletal muscle aging and motor deficits by activating the AMPK signaling pathway.

Tetramethylpyrazine nitrone (TBN), a novel derivative of tetramethylpyrazine (TMP) designed and synthesized by our group, possesses multi-functional mechanisms of action and displays broad protective effects in vitro and in animal models of age-related brain disorders such as stroke, Alzheimer's disease (AD), Amyotrophic Lateral Sclerosis (ALS) and Parkinson's disease (PD). In the present report, we investigated the effects of TBN on aging, specifically on muscle aging and the associated decline of motor functions. Using a D-galactose-induced aging mouse model, we found that TBN could reverse the levels of several senescence and aging markers including p16, p21, ceramides, and telomere length and increase the wet-weight ratio of gastrocnemius muscle tissue, demonstrating its efficacy in ameliorating muscle aging. Additionally, the pharmacological effects of TBN on motor deficits (gait analysis, pole-climbing test and grip strength test), muscle fibrosis (hematoxylin & eosin (HE), Masson staining, and αSMA staining), inflammatory response (IL-1ß, IL-6, and TNF-α), and mitochondrial function (ATP, mitochondrial membrane potential (MMP) and reactive oxygen species (ROS) were also confirmed in the D-galactose-induced aging models. Further experiments demonstrated that TBN alleviated muscle aging and improved the decline of age-related motor deficits through an AMPK-dependent mechanism. These findings highlight the significance of TBN as a potential anti-aging agent to combat the occurrence and development of aging and age-related diseases.

Genome-Wide Identification and Characterization of Long Non-Coding RNAs in Roots of Rice Seedlings under Nitrogen Deficiency.

Long non-coding RNAs (lncRNAs) regulate gene expression in eukaryotic organisms. Research suggests that lncRNAs may be involved in the regulation of nitrogen use efficiency in plants. In this study, we identified 1628 lncRNAs based on the transcriptomic sequencing of rice roots under low-nitrogen (LN) treatment through the implementation of an integrated bioinformatics pipeline. After 4 h of LN treatment, 50 lncRNAs and 373 mRNAs were significantly upregulated, and 17 lncRNAs and 578 mRNAs were significantly downregulated. After 48 h LN treatment, 43 lncRNAs and 536 mRNAs were significantly upregulated, and 42 lncRNAs and 947 mRNAs were significantly downregulated. Moreover, the interaction network among the identified lncRNAs and mRNAs was investigated and one of the LN-induced lncRNAs (lncRNA24320.6) was further characterized. lncRNA24320.6 was demonstrated to positively regulate the expression of a flavonoid 3'-hydroxylase 5 gene (OsF3'H5). The overexpression of lncRNA24320.6 was shown to improve nitrogen absorption and promote growth in rice seedlings under LN conditions. Our results provide valuable insights into the roles of lncRNAs in the rice response to nitrogen starvation.

Identification of Superior Haplotypes and Haplotype Combinations for Grain Size- and Weight-Related Genes for Breeding Applications in Rice (Oryza sativa L.).

The identification of superior haplotypes and haplotype combinations is essential for haplotype-based breeding (HBB), which provides selection targets for genomics-assisted breeding. In this study, genotypes of 42 functional genes in rice were analyzed by targeted capture sequencing in a panel of 180 Indica rice accessions. In total, 69 SNPs/Indels in seven genes were detected to be associated with grain length (GL), grain width (GW), ratio of grain length-width (L/W) and thousand-grain weight (TGW) using candidate gene-based association analysis, including BG1 and GS3 for GL, GW5 for GW, BG1 and GW5 for L/W, and AET1, SNAC1, qTGW3, DHD1 and GW5 for TGW. Furthermore, two haplotypes were identified for each of the seven genes according to these associated SNPs/Indels, and the amount of genetic variation explained by different haplotypes ranged from 3.24% to 27.66%. Additionally, three, three and eight haplotype combinations for GL, L/W and TGW explained 25.38%, 5.5% and 22.49% of the total genetic variation for each trait, respectively. Further analysis showed that Minghui63 had the superior haplotype combination Haplotype Combination 4 (HC4) for TGW. The most interesting finding was that some widely used restorer lines derived from Minghui63 also have the superior haplotype combination HC4, and our breeding varieties and lines using the haplotype-specific marker panel also confirmed that the TGW of the lines was much higher than that of their sister lines without HC4, suggesting that TGW-HC4 is the superior haplotype combination for TGW and can be utilized in rice breeding.

Strategies targeting endoplasmic reticulum stress to improve Parkinson's disease.

Parkinson's disease (PD) is a common neurodegenerative disorder with motor symptoms, which is caused by the progressive death of dopaminergic (DA) neurons in the substantia nigra pars compacta (SNpc). Accumulating evidence shows that endoplasmic reticulum (ER) stress occurring in the SNpc DA neurons is an early event in the development of PD. ER stress triggers the activation of unfolded protein response (UPR) to reduce stress and restore ER function. However, excessive and continuous ER stress and UPR exacerbate the risk of DA neuron death through crosstalk with other PD events. Thus, ER stress is considered a promising therapeutic target for the treatment of PD. Various strategies targeting ER stress through the modulation of UPR signaling, the increase of ER's protein folding ability, and the enhancement of protein degradation are developed to alleviate neuronal death in PD models. In this review, we summarize the pathological role of ER stress in PD and update the strategies targeting ER stress to improve ER protein homeostasis and PD-related events.

Tetramethylpyrazine nitrone exerts neuroprotection via activation of PGC-1α/Nrf2 pathway in Parkinson's disease models.

INTRODUCTION: Parkinson's disease (PD) is common neurodegenerative disease where oxidative stress and mitochondrial dysfunction play important roles in its progression. Tetramethylpyrazine nitrone (TBN), a potent free radical scavenger, has shown protective effects in various neurological conditions. However, the neuroprotective mechanisms of TBN in PD models remain unclear. OBJECTIVES: We aimed to investigate TBN's neuroprotective effects and mechanisms in PD models. METHODS: TBN's neuroprotection was initially measured in MPP+/MPTP-induced PD models. Subsequently, a luciferase reporter assay was used to detect peroxisome proliferator-activated receptor γ co-activator 1α (PGC-1α) promoter activity. Effects of TBN on antioxidant damage and the PGC-1α/Nuclear factor erythroid-2-related factor 2 (Nrf2) pathway were thoroughly investigated. RESULTS: In MPP+-induced cell model, TBN (30-300 µM) increased cell survival by 9.95 % (P < 0.05), 16.63 % (P < 0.001), and 24.09 % (P < 0.001), respectively. TBN enhanced oxidative phosphorylation (P < 0.05) and restored PGC-1α transcriptional activity suppressed by MPP+ (84.30 % vs 59.03 %, P < 0.01). In MPTP-treated mice, TBN (30 mg/kg) ameliorated motor impairment, increased striatal dopamine levels (16.75 %, P < 0.001), dopaminergic neurons survival (27.12 %, P < 0.001), and tyrosine hydroxylase expression (28.07 %, P < 0.01). Selegiline, a positive control, increased dopamine levels (15.35 %, P < 0.001) and dopaminergic neurons survival (25.34 %, P < 0.001). Additionally, TBN reduced oxidative products and activated the PGC-1α/Nrf2 pathway. PGC-1α knockdown diminished TBN's neuroprotective effects, decreasing cell viability from 73.65 % to 56.87 % (P < 0.001). CONCLUSION: TBN has demonstrated consistent effectiveness in MPP+-induced midbrain neurons and MPTP-induced mice. Notably, the therapeutic effect of TBN in mitigating motor deficits and neurodegeneration is superior to selegiline. The neuroprotective mechanisms of TBN are associated with activation of the PGC-1α/Nrf2 pathway, thereby reducing oxidative stress and maintaining mitochondrial function. These findings suggest that TBN may be a promising therapeutic candidate for PD, warranting further development and investigation.

Iterated Clique Reductions in Vertex Weighted Coloring for Large Sparse Graphs.

The Minimum Vertex Weighted Coloring (MinVWC) problem is an important generalization of the classic Minimum Vertex Coloring (MinVC) problem which is NP-hard. Given a simple undirected graph G=(V,E), the MinVC problem is to find a coloring s.t. any pair of adjacent vertices are assigned different colors and the number of colors used is minimized. The MinVWC problem associates each vertex with a positive weight and defines the weight of a color to be the weight of its heaviest vertices, then the goal is the find a coloring that minimizes the sum of weights over all colors. Among various approaches, reduction is an effective one. It tries to obtain a subgraph whose optimal solutions can conveniently be extended into optimal ones for the whole graph, without costly branching. In this paper, we propose a reduction algorithm based on maximal clique enumeration. More specifically our algorithm utilizes a certain proportion of maximal cliques and obtains lower bounds in order to perform reductions. It alternates between clique sampling and graph reductions and consists of three successive procedures: promising clique reductions, better bound reductions and post reductions. Experimental results show that our algorithm returns considerably smaller subgraphs for numerous large benchmark graphs, compared to the most recent method named RedLS. Also, we evaluate individual impacts and some practical properties of our algorithm. Furthermore, we have a theorem which indicates that the reduction effects of our algorithm are equivalent to that of a counterpart which enumerates all maximal cliques in the whole graph if the run time is sufficiently long.

Comprehensive identification and characterization of lncRNAs and circRNAs reveal potential brown planthopper-responsive ceRNA networks in rice.

Brown planthopper (Nilaparvata lugens Stål, BPH) is one of the most destructive pests of rice. Non-coding RNA plays an important regulatory role in various biological processes. However, comprehensive identification and characterization of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in BPH-infested rice have not been performed. Here, we performed a genome-wide analysis of lncRNAs and circRNAs in BPH6-transgenic (resistant, BPH6G) and Nipponbare (susceptible, NIP) rice plants before and after BPH feeding (early and late stage) via deep RNA-sequencing. A total of 310 lncRNAs and 129 circRNAs were found to be differentially expressed. To reveal the different responses of resistant and susceptible rice to BPH herbivory, the potential functions of these lncRNAs and circRNAs as competitive endogenous RNAs (ceRNAs) were predicted and investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Dual-luciferase reporter assays revealed that miR1846c and miR530 were targeted by the lncRNAs XLOC_042442 and XLOC_028297, respectively. In responsive to BPH infestation, 39 lncRNAs and 21 circRNAs were predicted to combine with 133 common miRNAs and compete for miRNA binding sites with 834 mRNAs. These mRNAs predictably participated in cell wall organization or biogenesis, developmental growth, single-organism cellular process, and the response to stress. This study comprehensively identified and characterized lncRNAs and circRNAs, and integrated their potential ceRNA functions, to reveal the rice BPH-resistance network. These results lay a foundation for further study on the functions of lncRNAs and circRNAs in the rice-BPH interaction, and enriched our understanding of the BPH-resistance response in rice.

Chrysin prevents inflammation-coinciding liver steatosis via AMPK signalling.

OBJECTIVES: We aimed to elucidate the therapeutic potential of Chrysin (CN) against the high-fat diet (HFD) induced non-alcoholic fatty liver disease (NAFLD) and its mechanism. METHODS: To assess the hypothesis, NAFLD was induced in C57BL/6 mice by feeding a high-fat diet for up to two months, followed by CN administration (for three months). Liver injury/toxicity, lipid deposition, inflammation and fibrosis were detected via molecular and biochemical analysis, including blood chemistry, immunoimaging and immunoblotting. Moreover, we performed proteomic analysis to illuminate Chrysin's therapeutic effects further. KEY FINDINGS: CN treatment significantly reduced liver-fat accumulation and inflammation, ultimately improving obesity and liver injury in NAFLD mice. Proteomic analysis showed that CN modified the protein expression profiles in the liver, particularly improving the expression of proteins related to energy, metabolism and inflammation. Mechanistically, CN treatment increased AMP-activated protein and phosphorylated CoA (P-ACC). Concurrently, it reduced inflammation and inflammation activation by inhibiting NLRP3 expression. CONCLUSIONS: In summary, CN treatment reduced lipid metabolism by AMPK and inflammasome activation by NLRP3 inhibition, ultimately improving NAFLD progression. These findings suggest that CN could be a potential treatment candidate for the NFLAD condition.

Multiomics analysis of human peripheral blood reveals marked molecular profiling changes caused by one night of sleep deprivation.

Sleep insufficiency is associated with various disorders; the molecular basis is unknown until now. Here, 14 males and 18 females were subjected to short-term (24 h) sleep deprivation, and donated fasting blood samples prior to (day 1) and following (days 2 and 3) short-term sleep deprivation. We used multiple omics techniques to examine changes in volunteers' blood samples that were subjected to integrated, biochemical, transcriptomic, proteomic, and metabolomic analyses. Sleep deprivation caused marked molecular changes (46.4% transcript genes, 59.3% proteins, and 55.6% metabolites) that incompletely reversed by day 3. The immune system in particular neutrophil-mediated processes associated with plasma superoxidase dismutase-1 and S100A8 gene expression was markedly affected. Sleep deprivation decreased melatonin levels and increased immune cells, inflammatory factors and c-reactive protein. By disease enrichment analysis, sleep deprivation induced signaling pathways for schizophrenia and neurodegenerative diseases enriched. In sum, this is the first multiomics approach to show that sleep deprivation causes prominent immune changes in humans, and clearly identified potential immune biomarkers associated with sleep deprivation. This study indicated that the blood profile following sleep disruption, such as may occur among shift workers, may induce immune and central nervous system dysfunction.

Adiponectin deficiency accelerates brain aging via mitochondria-associated neuroinflammation.

BACKGROUND: A wide spectrum of changes occurs in the brain with age, from molecular to morphological aspects, and inflammation accompanied by mitochondria dysfunction is one of the significant factors associated with age. Adiponectin (APN), an essential adipokine in glucose and lipid metabolism, is involved in the aging; however, its role in brain aging has not been adequately explored. Here, we aimed to explore the relationship between APN deficiency and brain aging using multiple biochemical and pharmacological methods to probe APN in humans, KO mice, primary microglia, and BV2 cells. RESULTS: We found that declining APN levels in aged human subjects correlated with dysregulated cytokine levels, while APN KO mice exhibited accelerated aging accompanied by learning and memory deficits, anxiety-like behaviors, neuroinflammation, and immunosenescence. APN-deficient mice displayed aggravated mitochondrial dysfunction and HDAC1 upregulation. In BV2 cells, the APN receptor agonist AdipoRon alleviated the mitochondrial deficits and aging markers induced by rotenone or antimycin A. HDAC1 antagonism by Compound 60 (Cpd 60) improved mitochondrial dysfunction and age-related inflammation, as validated in D-galactose-treated APN KO mice. CONCLUSION: These findings indicate that APN is a critical regulator of brain aging by preventing neuroinflammation associated with mitochondrial impairment via HDAC1 signaling.

Acetylated tau exacerbates learning and memory impairment by disturbing with mitochondrial homeostasis.

Increased tau acetylation at K274 and K281 has been observed in the brains of Alzheimer's disease (AD) patients and animal models, and mitochondrial dysfunction are noticeable and early features of AD. However, the effect of acetylated tau on mitochondria has been unclear until now. Here, we constructed three type of tau forms, acetylated tau mutant by mutating its K274/K281 into Glutamine (TauKQ) to mimic disease-associated lysine acetylation, the non-acetylation tau mutant by mutating its K274/K281 into Arginine (TauKR) and the wild-type human full-length tau (TauWT). By overexpression of these tau forms in vivo and in vitro, we found that, TauKQ induced more severe cognitive deficits with neuronal loss, dendritic plasticity damage and mitochondrial dysfunctions than TauWT. Unlike TauWT induced mitochondria fusion, TauKQ not only induced mitochondria fission by decreasing mitofusion proteins, but also inhibited mitochondrial biogenesis via reduction of PGC-1a/Nrf1/Tfam levels. TauKR had no significant difference in the cognitive and mitochondrial abnormalities compared with TauWT. Treatment with BGP-15 rescued impaired learning and memory by attenuation of mitochondrial dysfunction, neuronal loss and dendritic complexity damage, which caused by TauKQ. Our data suggested that, acetylation at K274/281 was an important post translational modification site for tau neurotoxicity, and BGP-15 is a potential therapeutic drug for AD.

Evaluation of therapeutic effects of tetramethylpyrazine nitrone in Alzheimer's disease mouse model and proteomics analysis.

The pathophysiology of Alzheimer's disease (AD) is multifactorial with characteristic extracellular accumulation of amyloid-beta (Aß) and intraneuronal aggregation of hyperphosphorylated tau in the brain. Development of disease-modifying treatment for AD has been challenging. Recent studies suggest that deleterious alterations in neurovascular cells happens in parallel with Aß accumulation, inducing tau pathology and necroptosis. Therefore, therapies targeting cellular Aß and tau pathologies may provide a more effective strategy of disease intervention. Tetramethylpyrazine nitrone (TBN) is a nitrone derivative of tetramethylpyrazine, an active ingredient from Ligusticum wallichii Franchat (Chuanxiong). We previously showed that TBN is a potent scavenger of free radicals with multi-targeted neuroprotective effects in rat and monkey models of ischemic stroke. The present study aimed to investigate the anti-AD properties of TBN. We employed AD-related cellular model (N2a/APPswe) and transgenic mouse model (3×Tg-AD mouse) for mechanistic and behavioral studies. Our results showed that TBN markedly improved cognitive functions and reduced Aß and hyperphosphorylated tau levels in mouse model. Further investigation of the underlying mechanisms revealed that TBN promoted non-amyloidogenic processing pathway of amyloid precursor protein (APP) in N2a/APPswe in vitro. Moreover, TBN preserved synapses from dendritic spine loss and upregulated synaptic protein expressions in 3×Tg-AD mice. Proteomic analysis of 3×Tg-AD mouse hippocampal and cortical tissues showed that TBN induced neuroprotective effects through modulating mitophagy, MAPK and mTOR pathways. In particular, TBN significantly upregulated PINK1, a key protein for mitochondrial homeostasis, implicating PINK1 as a potential therapeutic target for AD. In summary, TBN improved cognitive functions in AD-related mouse model, inhibited Aß production and tau hyperphosphorylation, and rescued synaptic loss and neuronal damage. Multiple mechanisms underlie the anti-AD effects of TBN including the modulation of APP processing, mTOR signaling and PINK1-related mitophagy.

Deep Learning of Phase-Contrast Images of Cancer Stem Cells Using a Selected Dataset of High Accuracy Value Using Conditional Generative Adversarial Networks.

Artificial intelligence (AI) technology for image recognition has the potential to identify cancer stem cells (CSCs) in cultures and tissues. CSCs play an important role in the development and relapse of tumors. Although the characteristics of CSCs have been extensively studied, their morphological features remain elusive. The attempt to obtain an AI model identifying CSCs in culture showed the importance of images from spatially and temporally grown cultures of CSCs for deep learning to improve accuracy, but was insufficient. This study aimed to identify a process that is significantly efficient in increasing the accuracy values of the AI model output for predicting CSCs from phase-contrast images. An AI model of conditional generative adversarial network (CGAN) image translation for CSC identification predicted CSCs with various accuracy levels, and convolutional neural network classification of CSC phase-contrast images showed variation in the images. The accuracy of the AI model of CGAN image translation was increased by the AI model built by deep learning of selected CSC images with high accuracy previously calculated by another AI model. The workflow of building an AI model based on CGAN image translation could be useful for the AI prediction of CSCs.

Initial Solution Generation and Diversified Variable Picking in Local Search for (Weighted) Partial MaxSAT.

The (weighted) partial maximum satisfiability ((W)PMS) problem is an important generalization of the classic problem of propositional (Boolean) satisfiability with a wide range of real-world applications. In this paper, we propose an initialization and a diversification strategy to improve local search for the (W)PMS problem. Our initialization strategy is based on a novel definition of variables' structural entropy, and it aims to generate a solution that is close to a high-quality feasible one. Then, our diversification strategy picks a variable in two possible ways, depending on a parameter: continuing to pick variables with the best benefits or focusing on a clause with the greatest penalty and then selecting variables probabilistically. Based on these strategies, we developed a local search solver dubbed ImSATLike, as well as a hybrid solver ImSATLike-TT, and experimental results on (weighted) partial MaxSAT instances in recent MaxSAT Evaluations show that they outperform or have nearly the same performances as state-of-the-art local search and hybrid competitors, respectively, in general. Furthermore, we carried out experiments to confirm the individual impacts of each proposed strategy.

Tetramethylpyrazine nitrone activates hypoxia-inducible factor and regulates iron homeostasis to improve renal anemia.

Renal anemia is one of the most common complications of chronic kidney disease and diabetic kidney disease. Despite the progress made in recent years, there is still an urgent unmet clinical need for renal anemia treatment. In this research, we investigated the efficacy and mechanism of action of the novel tetramethylpyrazine nitrone (TBN). Animal models of anemia including the streptozotocin (STZ)-induced spontaneously hypertensive rats (SHR) and the cisplatin (CDDP)-induced C57BL/6J mice are established to study the TBN's effects on expression of hypoxia-inducible factor and erythropoietin. To explore the mechanism of TBN's therapeutic effect on renal anemia, cobalt chloride (CoCl2) is used in Hep3B/HepG2 cells to simulate a hypoxic environment. TBN is found to increase the expression of hypoxia-inducible factor HIF-1α and HIF-2α under hypoxic conditions and reverse the reduction of HIFs expression caused by saccharate ferric oxide (SFO). TBN also positively regulates the AMPK pathway. TBN stimulates nuclear transcription and translation of erythropoietin by enhancing the stability of HIF-1α expression. TBN has a significant regulatory effect on several major biomarkers of iron homeostasis, including ferritin, ferroportin (FPN), and divalent metal transporter-1 (DMT1). In conclusion, TBN regulates the AMPK/mTOR/4E-BP1/HIFs pathway, and activates the hypoxia-inducible factor and regulates iron homeostasis to improve renal anemia.

Memantine nitrate MN-08 suppresses NLRP3 inflammasome activation to protect against sepsis-induced acute lung injury in mice.

Sepsis is a life-threatening organ dysfunction with devastating consequences, prominent among which is lung damage. Memantine, an N-methyl-D-aspartic acid receptor (NMDAR) antagonist, is able to alleviate acute lung injury (ALI). Nitric oxide (NO) suppresses NLRP3 inflammasome activation against lipopolysaccharide (LPS)-induced septic shock. MN-08, a novel nitrate derivative of memantine, possesses both the ability to antagonize NMDAR and release NO. In the present study, we aimed to investigate the protective effects of MN-08 against LPS-induced systemic inflammation and septic lung injury in mice, and to explore the underlying mechanisms of MN-08 in LPS-induced mice and THP-1 macrophages. MN-08 significantly increased the survival rate of septic mice, alleviated LPS-induced sepsis in mice via improving systemic inflammatory response syndrome and immune dysfunction, and attenuated pulmonary injury and inflammatory infiltration. More importantly, the therapeutic benefit of MN-08 for sepsis was greater than that of memantine and dexamethasone. Mechanistically, MN-08 exerted anti-inflammatory activity through inhibiting nuclear translocation of NF-κB, activation of the MAPK signaling pathway and the signaling transduction of STAT3/NF-κB. In addition, MN-08 suppressed NLRP3 inflammasome activation. Taken together, our studies demonstrate that MN-08 may be a promising therapeutic agent for sepsis-induced acute lung injury.

Comparison and Analysis of Several Clustering Algorithms for Pavement Crack Segmentation Guided by Computational Intelligence.

Cracks are one of the most common types of imperfections that can be found in concrete pavement, and they have a significant influence on the structural strength. The purpose of this study is to investigate the performance differences of various spatial clustering algorithms for pavement crack segmentation and to provide some reference for the work that is being done to maintain pavement currently. This is done by comparing and analyzing the performance of complex crack photos in different settings. For the purpose of evaluating how well the comparison method works, the indices of evaluation of NMI and RI have been selected. The experiment also includes a detailed analysis and comparison of the noisy photographs. According to the results of the experiments, the segmentation effect of these cluster algorithms is significantly worse after adding Gaussian noise; based on the NMI value, the mean-shift clustering algorithm has the best de-noise effect, whereas the performance of some clustering algorithms significantly decreases after adding noise.