Catalpol reduced LPS induced BV2 immunoreactivity through NF-κB/NLRP3 pathways: an in Vitro and in silico study

Background: Ischemic Stroke (IS) stands as one of the primary cerebrovascular diseases profoundly linked with inflammation. In the context of neuroinflammation, an excessive activation of microglia has been observed. Consequently, regulating microglial activation emerges as a vital target for neuroinflammation treatment. Catalpol (CAT), a natural compound known for its anti-inflammatory properties, holds promise in this regard. However, its potential to modulate neuroinflammatory responses in the brain, especially on microglial cells, requires comprehensive exploration.Methods: In our study, we investigated into the potential anti-inflammatory effects of catalpol using lipopolysaccharide (LPS)-stimulated BV2 microglial cells as an experimental model. The production of nitric oxide (NO) by LPS-activated BV2 cells was quantified using the Griess reaction. Immunofluorescence was employed to measure glial cell activation markers. RT-qPCR was utilized to assess mRNA levels of various inflammatory markers. Western blot analysis examined protein expression in LPS-activated BV2 cells. NF-κB nuclear localization was detected by immunofluorescent staining. Additionally, molecular docking and molecular dynamics simulations (MDs) were conducted to explore the binding affinity of catalpol with key targets.Results: Catalpol effectively suppressed the production of nitric oxide (NO) induced by LPS and reduced the expression of microglial cell activation markers, including Iba-1. Furthermore, we observed that catalpol downregulated the mRNA expression of proinflammatory cytokines such as IL-6, TNF-α, and IL-1β, as well as key molecules involved in the NLRP3 inflammasome and NF-κB pathway, including NLRP3, NF-κB, caspase-1, and ASC. Our mechanistic investigations shed light on how catalpol operates against neuroinflammation. It was evident that catalpol significantly inhibited the phosphorylation of NF-κB and NLRP3 inflammasome activation, both of which serve as upstream regulators of the inflammatory cascade. Molecular docking and MDs showed strong binding interactions between catalpol and key targets such as NF-κB, NLRP3, and IL-1β.Conclusion: Our findings support the idea that catalpol holds the potential to alleviate neuroinflammation, and it is achieved by inhibiting the activation of NLRP3 inflammasome and NF-κB, ultimately leading to the downregulation of pro-inflammatory cytokines. Catalpol emerges as a promising candidate for the treatment of neuroinflammatory conditions

The effect of Dnaaf5 gene dosage on primary ciliary dyskinesia phenotypes

DNAAF5 is a dynein motor assembly factor associated with the autosomal heterogenic recessive condition of motile cilia, primary ciliary dyskinesia (PCD). The effects of allele heterozygosity on motile cilia function are unknown. We used CRISPR-Cas9 genome editing in mice to recreate a human missense variant identified in patients with mild PCD and a second, frameshift-null deletion in Dnaaf5. Litters with Dnaaf5 heteroallelic variants showed distinct missense and null gene dosage effects. Homozygosity for the null Dnaaf5 alleles was embryonic lethal. Compound heterozygous animals with the missense and null alleles showed severe disease manifesting as hydrocephalus and early lethality. However, animals homozygous for the missense mutation had improved survival, with partially preserved cilia function and motor assembly observed by ultrastructure analysis. Notably, the same variant alleles exhibited divergent cilia function across different multiciliated tissues. Proteomic analysis of isolated airway cilia from mutant mice revealed reduction in some axonemal regulatory and structural proteins not previously reported in DNAAF5 variants. Transcriptional analysis of mouse and human mutant cells showed increased expression of genes coding for axonemal proteins. These findings suggest allele-specific and tissue-specific molecular requirements for cilia motor assembly that may affect disease phenotypes and clinical trajectory in motile ciliopathies

Rapid detection of multiple resistance genes to last-resort antibiotics in Enterobacteriaceae pathogens by recombinase polymerase amplification combined with lateral flow dipstick

The worrying emergence of multiple resistance genes to last-resort antibiotics in food animals and human populations throughout the food chain and relevant environments has been increasingly reported worldwide. Enterobacteriaceae pathogens are considered the most common reservoirs of such antibiotic resistance genes (ARGs). Thus, a rapid, efficient and accurate detection method to simultaneously screen and monitor such ARGs in Enterobacteriaceae pathogens has become an urgent need. Our study developed a recombinase polymerase amplification (RPA) assay combined with a lateral flow dipstick (LFD) for simultaneously detecting predominant resistance genes to last-resort antibiotics of Enterobacteriaceae pathogens, including mcr-1, blaNDM-1 and tet(X4). It is allowed to complete the entire process, including crude DNA extraction, amplification as well as reading, within 40 min at 37°C, and the detection limit is 101 copies/μl for mcr-1, blaNDM-1 and tet(X4). Sensitivity analysis showed obvious association of color signals with the template concentrations of mcr-1, blaNDM-1 and tet(X4) genes in Enterobacteriaceae pathogens using a test strip reader (R2 = 0.9881, R2 = 0.9745, and R2 = 0.9807, respectively), allowing for quantitative detection using multiplex RPA-LFD assays. Therefore, the RPA-LFD assay can suitably help to detect multiple resistance genes to last-resort antibiotics in foodborne pathogens and has potential applications in the field

NGF rapidly increases membrane expression of TRPV1 heat-gated ion channels

Nociceptors, or pain-sensitive receptors, are unique among sensory receptors in that their sensitivity is increased by noxious stimulation. This process, called sensitization or hyperalgesia, is mediated by a variety of proinflammatory factors, including bradykinin, ATP and NGF, which cause sensitization to noxious heat stimuli by enhancing the membrane current carried by the heat- and capsaicin-gated ion channel, TRPV1. Several different mechanisms for sensitization of TRPV1 have been proposed. Here we show that NGF, acting on the TrkA receptor, activates a signalling pathway in which PI3 kinase plays a crucial early role, with Src kinase as the downstream element which binds to and phosphorylates TRPV1. Phosphorylation of TRPV1 at a single tyrosine residue, Y200, followed by insertion of TRPV1 channels into the surface membrane, explains most of the rapid sensitizing actions of NGF

Inflammatory Pain: The Cellular Basis of Heat Hyperalgesia

Injury or inflammation release a range of inflammatory mediators that increase the sensitivity of sensory neurons to noxious thermal or mechanical stimuli. The heat- and capsaicin-gated channel TRPV1, which is an important detector of multiple noxious stimuli, plays a critical role in the development of thermal hyperalgesia induced by a wide range of inflammatory mediators. We review here recent findings on the molecular mechanisms of sensitisation of TRPV1 by inflammatory mediators, including bradykinin, ATP, NGF and prostaglandins. We describe the signalling pathways believed to be involved in the potentiation of TRPV1, and our current understanding of how inflammatory mediators couple to these pathways

Modulation of temperature-sensitive TRP channels

Animals sense temperature – either cold or hot – by the direct activation of temperature-sensitive members of the TRP family of ion channels, the thermo-TRPs. To date, six TRP channels – TRPV1–4, TRPM8 and TRPA1 – have been reported to be directly activated by heat and to be involved in thermosensation. Temperature sensing can be modulated by phosphorylation of intracellular residues by protein kinases or by insertion of new channels into the cell membrane. In this review we provide a brief overview of the properties of thermo-TRPs, and we summarise signalling pathways involved in their regulation

Research on Green Building Design Optimization Based on Building Information Modeling and Improved Genetic Algorithm

The energy consumption of the construction industry has been increasing year by year, posing a huge challenge to China’s dual carbon goals of peaking carbon emissions and achieving carbon neutrality. The Chinese construction industry has huge potential for energy conservation and emission reduction, and the government has therefore put forward requirements for constructing green buildings and formulated strict evaluation standards. The carbon emissions of the construction industry involve various stages of the entire life cycle and are closely related to the green building design standards that meet the requirements. This article sets multiple objective functions based on the two dimensions of the carbon emissions of the entire life cycle of buildings and green building evaluation and uses the NSGA-II algorithm in genetic algorithms to optimize ten indicators selected from the two objectives. Based on this, building information modeling (BIM) modeling was carried out for an office building project in Southwest China, and energy consumption analysis and evaluation were conducted based on the project’s multidisciplinary model. The dialectical relationship between the carbon emissions of the entire life cycle of buildings and the green building evaluation values was discovered, and the optimized parameter combination scheme corresponding to the Pareto solution set was obtained, providing a reference for using improved genetic algorithms and BIM technology to optimize green building design

Purification, Characterization, and Mode of Action of Pentocin JL-1, a Novel Bacteriocin Isolated from Lactobacillus pentosus, against Drug-Resistant Staphylococcus aureus

Staphylococcus aureus and its drug-resistant strains, which threaten public health and food safety, are in need of effective control by biopreservatives. A novel bacteriocin, pentocin JL-1, produced by Lactobacillus pentosus that was isolated from the intestinal tract of Chiloscyllium punctatum, was purified by a four-step chromatographic process. Mass spectrometry based on MALDI-TOF indicated that pentocin JL-1 has a molecular mass of 2987.23 Da. Only six of the twenty-five amino acids could be identified by Edman degradation. This bacteriocin is thermostable and tolerates a pH range of 5–7. Also, it is sensitive to proteinase K, trypsin, pepsin, and alkaline protease. This bacteriocin has a broad inhibitory spectrum against both Gram-positive and Gram-negative strains and in particular is effective against multidrug-resistant S. aureus. Additionally, we showed that the cell membrane is the target of pentocin JL-1 against methicillin-resistant S. aureus (MRSA), causing a loss of proton motive force. Furthermore, pentocin JL-1 has a drastic impact on the structure and integrity of MRSA cells. These results suggest that pentocin JL-1 has potential as a biopreservative in the food industry

A Tightly Integrated Navigation Method of SINS, DVL, and PS Based on RIMM in the Complex Underwater Environment

Navigation and positioning of autonomous underwater vehicles (AUVs) in the complex and changeable marine environment are crucial and challenging. For the positioning of AUVs, the integrated navigation of the strap-down inertial navigation system (SINS), Doppler velocity log (DVL), and pressure sensor (PS) has a common application. Nevertheless, in the complex underwater environment, the DVL performance is affected by the current and complex terrain environments. The outliers in sensor observations also have a substantial adverse effect on the AUV positioning accuracy. To address these issues, in this paper, a novel tightly integrated navigation model of the SINS, DVL, and PS is established. In contrast to the traditional SINS, DVL, and PS tightly integrated navigation methods, the proposed method in this paper is based on the velocity variation of the DVL beam by applying the DVL bottom-track and water-track models. Furthermore, a new robust interacting multiple models (RIMM) information fusion algorithm is proposed. In this algorithm, DVL beam anomaly is detected, and the Markov transfer probability matrix is accordingly updated to enable quick model matching. By simulating the motion of the AUV in a complex underwater environment, we also compare the performance of the traditional loosely integrated navigation (TLIN) model, the tightly integrated navigation (TTIN) model, and the IMM algorithm. The simulation results show that because of the PS, the velocity and height in the up-change amplitude of the four algorithms are small. Compared with the TLIN algorithm in terms of maximum deviation of latitude and longitude, the RIMM algorithm also improves the accuracy by 39.1243 m and 26.4364 m, respectively. Furthermore, compared with the TTIN algorithm, the RIMM algorithm improves latitude and longitude accuracy by 1.8913 m and 11.8274 m, respectively. A comparison with IMM also shows that RIMM improves the accuracy of latitude and longitude by 1.1506 m and 7.2301 m, respectively. The results confirm that the proposed algorithm suppresses the observed noise and outliers of DVL and further achieves quick conversion between different DVL models while making full use of the effective information of the DVL beams. The proposed method also improves the navigation accuracy of AUVs in complex underwater environments