Genetically engineered cell membrane-coated nanoparticles for antibacterial and immunoregulatory dual-function treatment of ligature-induced periodontitis

Purpose: In order to overcome the problem that conventional pharmacological treatments of periodontitis cannot effectively synergizing antimicrobial and immunomodulation, inspired by the critical role of toll-like receptor 4 (TLR4) in bacterial recognition and immune activation, we demonstrated a combined antibacterial-immunoregulatory strategy based on biomimetic nanoparticles.Methods: Functioned cell membranes and silk fibroin nanoparticles (SNs) loaded with minocycline hydrochloride (Mino) were used to prepare a biomimetic nanoparticle (MSNCs). SNs and MSNCs were characterized by Scanning Electron Microscope, size, zeta potential, dispersion index. At the same time, SNs were characterized by cell counting kit-8 and real-time Polymerase Chain Reaction (RT-PCR). TLR4-expressing cell membranes were characterized by RT-PCR and western blot (WB). Cell membrane coating was characterized by Transmission Electron Microscope (TEM), the Bradford staining and WB. Then, Laser confocal, flow cytometry and agar plate coating were evaluated in vitro with antibacterial effects, RT-PCR was simultaneously evaluated with immunoregulatory effects. Finally, Anti-inflammatory treatment of MSNCs was evaluated in a ligature-induced periodontitis (LIP) mouse model.Results: Successfully prepared cell membranes overexpressing TLR4 and constructed MSNCs. In vitro studies had shown that MSNCs effectively targeted bacteria via TLR4 and acted as molecular decoys to competitively neutralize lipopolysaccharide (LPS) in the microenvironment as well as inhibit inflammatory activation of macrophages. In vivo, MSNCs effectively attenuated periodontal tissue inflammation and alveolar bone loss in a LIP mouse model.Conclusion: MSNCs have good targeted antibacterial and immunoregulatory effects, and provide a new and effective strategy for the treatment of periodontitis and have good potential for application in various types of pathogenic bacterial infections

Manipulating rhizosphere microorganisms to improve crop yield in saline-alkali soil: a study on soybean growth and development

IntroductionRhizosphere microorganisms can effectively promote the stress resistance of plants, and some beneficial rhizosphere microorganisms can significantly promote the growth of crops under salt stress, which has the potential to develop special microbial fertilizers for increasing the yield of saline-alkali land and provides a low-cost and environmentally friendly new strategy for improving the crop yield of saline-alkali cultivated land by using agricultural microbial technology.MethodsIn May 2022, a field study in a completely randomized block design was conducted at the Heilongjiang Academy of Agricultural Sciences to explore the correlation between plant rhizosphere microorganisms and soybean growth in saline-alkali soil. Two soybean cultivars (Hening 531, a salt-tolerant variety, and 20_1846, a salt-sensitive variety) were planted at two experimental sites [Daqing (normal condition) and Harbin (saline-alkali conditions)], aiming to investigate the performance of soybean in saline-alkali environments.ResultsSoybeans grown in saline-alkali soil showed substantial reductions in key traits: plant height (25%), pod number (26.6%), seed yield (33%), and 100 seed weight (13%). This underscores the unsuitability of this soil type for soybean cultivation. Additionally, microbial analysis revealed 43 depleted and 56 enriched operational taxonomic units (OTUs) in the saline-alkali soil compared to normal soil. Furthermore, an analysis of ion-associated microbes identified 85 mOTUs with significant correlations with various ions. A co-occurrence network analysis revealed strong relationships between specific mOTUs and ions, such as Proteobacteria with multiple ions. In addition, the study investigated the differences in rhizosphere species between salt-tolerant and salt-sensitive soybean varieties under saline-alkali soil conditions. Redundancy analysis (RDA) indicated that mOTUs in saline-alkali soil were associated with pH and ions, while mOTUs in normal soil were correlated with Ca2+ and K+. Comparative analyses identified significant differences in mOTUs between salt-tolerant and salt-sensitive varieties under both saline-alkali and normal soil conditions. Planctomycetes, Proteobacteria, and Actinobacteria were dominant in the bacterial community of saline-alkali soil, with significant enrichment compared to normal soil. The study explored the functioning of the soybean rhizosphere key microbiome by comparing metagenomic data to four databases related to the carbon, nitrogen, phosphorus, and sulfur cycles. A total of 141 KOs (KEGG orthologues) were identified, with 66 KOs related to the carbon cycle, 16 KOs related to the nitrogen cycle, 48 KOs associated with the phosphorus cycle, and 11 KOs linked to the sulfur cycle. Significant correlations were found between specific mOTUs, functional genes, and phenotypic traits, including per mu yield (PMY), grain weight, and effective pod number per plant.ConclusionOverall, this study provides comprehensive insights into the structure, function, and salt-related species of soil microorganisms in saline-alkali soil and their associations with salt tolerance and soybean phenotype. The identification of key microbial species and functional categories offers valuable information for understanding the mechanisms underlying plant-microbe interactions in challenging soil conditions

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Comparative analysis of series fault arc detection methods

For uncertainty of line fault location, current series fault arc detection methods are mainly based on current signal analysis. By comparing current waveforms before and after series arc fault under different loads, characteristics and regularities of series fault arc current were obtained. Taking current signal of series fault arc as research object, three kinds of series fault arc detection methods were introduced which use Hilbert-Huang transform, information entropy and short-time Fourier transform and wavelet approximate entropy and support vector machine respectively. Extraction processes of fault arc feature with different detection methods were summarized, and advantages and disadvantages of the three methods were compared. A view was pointed out that the detection method based on Hilbert-Huang transform and the one based on information entropy and short-time Fourier transform can effectively extract time-frequency characteristics of fault arc, and series fault arc can be identified according to proper threshold of time-frequency spectrum amplitude with low accuracy and real-time performance. The detection method based on wavelet approximate entropy and support vector machine can directly extract approximate entropy as input of support vector machine to detect series fault arc with higher accuracy and real-time performance, which is more suitable for coal mine

AE Test of Calcareous Sands with Particle Rushing

The particle of calcareous sands was forced to crush, then the energy from the crushing was released by the form of sound waves. Therefore the AE technique was used to detect the calcareous sands AE signal when it crushed. by to study the AE characteristics, the mechanics of calcareous sands was studied. Study showed that: (1) there was the AE activities on the low confining pressure condition at the beginnig of test, (2) there was more and more AE activities with the continuing of test until to the end, (3) the calcareous sands’ AE activities was on the whole testing, (4) the calcareous sands’ particle crushing and mutual friction played different roles for its AE activities. Then the AE model based on the calcarous sands’ particle crushing was discussed

Comparative Study of Isoflavone Synthesis Genes in Two Wild Soybean Varieties Using Transcriptomic Analysis

Soybean is an important food crop that contains high amounts of isoflavones. However, due to the expression of multiple genes, different soybean seeds have different isoflavone compositions. The underlying mechanisms for this complexity remain unknown. In this study, we identified potential differentially expressed genes (DEGs) in two wild soybean cultivars, ZYD7068 (high isoflavone) and ZYD7194 (low isoflavone), at different seed developmental stages using RNA-seq technology and compared their differences in isoflavone content. A total of 1067 and 6479 differentially metabolized genes were identified at R6 and R8 stages, respectively. Subsequent analysis of the KEGG pathway revealed that three of these differential metabolized genes were involved in the Isoflavonoid biosynthesis and Flavone and flavonol biosynthesis at the R6 stage. A total of 80 TF genes encoding differential expression of MYB, bZIP, and WRKY were identified in A1 vs. B1 and A3 vs. B3. Eight differentially expressed genes were identified in duplicates at both stages, and three genes showed the same expression trend at both stages. To confirm the results of RNA-seq, qRT-PCR was performed to analyze the expression of the six identified differentially expressed genes (DEGs). The results of qRT-PCR were consistent with the results of RNA-seq. We found that four genes (Glyma.13G173300, Glyma.13G173600, Glyma.14G103100, and Glyma.17G158900) may be involved in the positive regulation of isoflavone synthesis, while two genes (Glyma.04G036700 and Glyma.19G030500) may be involved in the negative regulation of isoflavone synthesis. These findings suggest that the observed difference in isoflavone levels between the two cultivars may be attributable to the differential expression of these six genes at later stages of seed development