Budesonide and N-acetylcysteine inhibit activation of the NLRP3 inflammasome by regulating miR-381 to alleviate acute lung injury caused by the pyroptosis-mediated inflammatory response.

Background: The anti-inflammatory effects of budesonide (BUN) and N-acetylcysteine (NAC) attenuate acute lung injury (ALI). The aim of this study was to investigate the effects of combination therapy consisting of BUN and NAC on ALI and the underlying mechanisms. Methods: In vitro and in vivo models of ALI were generated by LPS induction. Western blotting was used to detect the expression levels of pyroptosis-related proteins and inflammation-related factors, and RT-qPCR was used to detect the expression of miR-381. Cell proliferation and apoptosis were detected by CCK-8 and flow cytometry, respectively. ELISA was used to detect the levels of inflammation-related factors. HE staining was used to detect lung injury. Results: The results showed that LPS effectively induced pyroptosis in cells and promoted the expression of pyroptosis-related proteins (Caspase1, Gasdermin D and NLRP3) and inflammatory cytokines (TNF-α, IL-6 and IL-1ß). The combination of BUN and NAC significantly alleviated LPS-induced pyroptosis and inflammation. In addition, the combination of BUN and NAC effectively promoted miR-381 expression. Transfection of miR-381 mimics effectively alleviated LPS-induced pyroptosis and inflammation, while transfection of miR-381 inhibitors had the opposite effect. miR-381 negatively regulates NLRP3 expression. Treatment with a miR-381 inhibitor or pc-NLRP3 reversed the effects of the combination of BUN and NAC. In a mouse model of ALI, the combination of BUN and NAC effectively improved lung injury, while treatment with a miR-381 inhibitor or pc-NLRP3 effectively reversed this effect. Conclusion: Overall, this study revealed that BUN + NAC inhibits the activation of NLRP3 by regulating miR-381, thereby alleviating ALI caused by pyroptosis-mediated inflammation.

Integration of molecular docking and molecular dynamics simulations with subtractive proteomics approach to identify the novel drug targets and their inhibitors in Streptococcus gallolyticus.

Streptococcus gallolyticus (Sg) is a non-motile, gram-positive bacterium that causes infective endocarditis (inflammation of the heart lining). Because Sg has gained resistance to existing antibiotics and there is currently no drug available, developing effective anti-Sg drugs is critical. This study combined core proteomics with a subtractive proteomics technique to identify potential therapeutic targets for Sg. Several bioinformatics approaches were used to eliminate non-essential and human-specific homologous sequences from the bacterial proteome. Then, virulence, druggability, subcellular localization, and functional analyses were carried out to specify the participation of significant bacterial proteins in various cellular processes. The pathogen's genome contained three druggable proteins, glucosamine-1phosphate N-acetyltransferase (GlmU), RNA polymerase sigma factor (RpoD), and pantetheine-phosphate adenylyltransferase (PPAT) which could serve as effective targets for developing novel drugs. 3D structures of target protein were modeled through Swiss Model. A natural product library containing 10,000 molecules from the LOTUS database was docked against therapeutic target proteins. Following an evaluation of the docking results using the glide gscore, the top 10 compounds docked against each protein receptor were chosen. LTS001632, LTS0243441, and LTS0236112 were the compounds that exhibited the highest binding affinities against GlmU, PPAT, and RpoD, respectively, among the compounds that were chosen. To augment the docking data, molecular dynamics simulations and MM-GBSA binding free energy were also utilized. More in-vitro research is necessary to transform these possible inhibitors into therapeutic drugs, though computer validations were employed in this study. This combination of computational techniques paves the way for targeted antibiotic development, which addresses the critical need for new therapeutic strategies against S. gallolyticus infections.

Stress mitigation mechanism of rice leaf microbiota amid atmospheric deposition of heavy metals.

Leaf microbiota have been extensively applied in the biological control of plant diseases, but their crucial roles in mitigating atmospheric heavy metal (HM) deposition and promoting plant growth remain poorly understood. This study demonstrates that elevated atmospheric HM deposition on rice leaves significantly shapes distinct epiphytic and endophytic microbiota across all growth stages. HM stress consistently leads to the dominance of epiphytic Pantoea and endophytic Microbacterium in rice leaves, particularly during the booting and filling stages. Leaf-bound HMs stimulate the differentiation of specialized microbial communities in both endophytic and epiphytic compartments, thereby regulating leaf microbial interactions. Metagenomic binning retrieved high-quality genomes of keystone leaf microorganisms, indicating their potential for essential metabolic functions. Notably, Pantoea and Microbacterium show significant HM resistance, plant growth-promoting capabilities, and diverse element cycling functions. They possess genes associated with metal(loid) resistance, such as ars and czc, suggesting their ability to detoxify arsenic(As) and cadmium(Cd). They also support carbon, nitrogen, and sulfur cycling, with genes linked to carbon fixation, nitrogen fixation, and sulfur reduction. Additionally, these bacteria may enhance plant stress resistance and growth by producing antioxidants, phytohormones, and other beneficial compounds, potentially improving HM stress tolerance and nutrient availability in rice plants. This study shows that atmospheric HMs affect rice leaf microbial communities, prompting plants to seek microbial help to combat stress. The unique composition and metabolic potential of rice leaf microbiota offer a novel perspective for mitigating adverse stress induced by atmospheric HM deposition. This contributes to the utilization of leaf microbiota to alleviate the negative impact of heavy metal deposition on rice development and food security.

Proteomics-based vaccine targets annotation and design of multi-epitope vaccine against antibiotic-resistant Streptococcus gallolyticus.

Streptococcus gallolyticus is a non-motile, gram-positive bacterium that causes infective endocarditis. S. gallolyticus has developed resistance to existing antibiotics, and no vaccine is currently available. Therefore, it is essential to develop an effective S. gallolyticus vaccine. Core proteomics was used in this study together with subtractive proteomics and reverse vaccinology approach to find antigenic proteins that could be utilized for the design of the S. gallolyticus multi-epitope vaccine. The pipeline identified two antigenic proteins as potential vaccine targets: penicillin-binding protein and the ATP synthase subunit. T and B cell epitopes from the specific proteins were forecasted employing several immunoinformatics and bioinformatics resources. A vaccine (360 amino acids) was created using a combination of seven cytotoxic T cell lymphocyte (CTL), three helper T cell lymphocyte (HTL), and five linear B cell lymphocyte (LBL) epitopes. To increase immune responses, the vaccine was paired with a cholera enterotoxin subunit B (CTB) adjuvant. The developed vaccine was highly antigenic, non-allergenic, and stable for human use. The vaccine's binding affinity and molecular interactions with the human immunological receptor TLR4 were studied using molecular mechanics/generalized Born surface area (MMGBSA), molecular docking, and molecular dynamic (MD) simulation analyses. Escherichia coli (strain K12) plasmid vector pET-28a ( +) was used to examine the ability of the vaccine to be expressed. According to the outcomes of these computer experiments, the vaccine is quite promising in terms of developing a protective immunity against diseases. However, in vitro and animal research are required to validate our findings.

A better method to evaluate the reliability of echocardiography for assessment of pulmonary hypertension: comparison of tricuspid regurgitant spectrum quality grading and tricuspid valve regurgitation degree.

Background: Transthoracic echocardiography (TTE) is recommended as the most important noninvasive screening tool for the diagnosis of pulmonary hypertension (PH), sonographers usually measure the volume of regurgitant flow rather than evaluating the spectral quality, so physicians will determine whether the ultrasound measurements of pulmonary arterial systolic pressure (US-PASP) are reliable based on the volume of tricuspid regurgitation (TR). Therefore, for the first time, we grade the quality of TR spectrum (TRS) based on its integrity and clarity, aiming to assess clinical application value of different tricuspid regurgitant spectrum quality grades (TR-SQG), and investigate whether the accuracy of US-PASP is more trustworthy than TR. Methods: We retrospectively analyzed 108 patients with chronic thromboembolic PH (CTEPH) to compare the correlation and agreement between US-PASP and right heart catheterization measurements of PASP (RHC-PASP). TR area (TRA) and TRS were measured in each patient, and TR-SQG was performed. Results: The correlation coefficients between US-PASP and RHC-PASP were r=0.622 (P<0.001), r=0.754 (P<0.001), r=0.595 (P<0.001) in mild, moderate, severe TR, and r=0.301 (P=0.135), r=0.747 (P<0.001), r=0.739 (P<0.001), r=0.828 (P<0.001) in TR-SQG I-IV, respectively. Bland-Altman analysis revealed the mean biases of 5.05, 3.06, 7.62 mmHg in mild, moderate, severe TR, and -16.47, -8.07, 1.82, 6.09 mmHg in TR-SQG I-IV, respectively. In mild TR with the TR-SQG III and IV, the correlation coefficients between US-PASP and RHC-PASP were r=0.779 (P<0.001), intraclass correlation coefficient (ICC) =0.774, paired t-test P=0.160, respectively; and the consistency was significantly higher than that of mild TR without considering TR-SQG. In moderate TR with the TR-SQG III and IV, the r=0.749, ICC =0.746, paired t-test P=0.298 between US-PASP and RHC-PASP. Conclusions: The US-PASP with TR-SQG III or IV is trustworthy, and its accuracy and consistency are better than those predicted by the traditional severity of TR. The establishment of the ultrasound evaluation system of TR-SQG helps clinicians to judge whether the US-PASP is accurate, credible, and reliable.

Evaluation of perceptual interactions between key aldehydes in Kung Pao Chicken.

Aldehydes are the strongest and most abundant aromatic compounds in Kung Pao Chicken. However, the perceptual interactions between these aldehydes are not fully understood. Therefore, the flavor contribution of nine key aldehydes was estimated by determining thresholds. Except for benzaldehyde, the thresholds of all aldehydes measured in tasteless chicken matrices (TM) were significantly larger than their comparable values in water. Based on these results, the perceptual interactions of nine aldehydes were evaluated using S-curves and σ-τ plots. The interactions indicated that 31 of their 36 binary mixtures exhibited additive effects, three had masking effects, while two had synergistic effects. Recombination experiments showed that the addition of aldehydes lowered the odor threshold of aldehyde reconstitution (AR), thereby enhancing the aroma intensity of AR. These findings contribute to a better understanding of Kung Pao Chicken's aroma and can be used to improve its aroma quality.

Integrating network pharmacology, molecular docking and simulation approaches with machine learning reveals the multi-target pharmacological mechanism of Berberis integerrima against diabetic nephropathy.

Diabetic nephropathy (DN) is one of the most feared complications of diabetes and key cause of end-stage renal disease (ESRD). Berberis integerrima has been widely used to treat diabetic complications, but exact molecular mechanism is yet to be discovered. Data on active ingredients of B. integerrima and target genes of both diabetic nephropathy and B.integerrima were obtained from public databases. Common results between B. integerrima and DN targets were used to create protein-protein interaction (PPI) network using STRING database and exported to Cytoscape software for the selection of hub genes based on degree of connectivity. Future, PPI network between constituents and overlapping targets was created using Cytoscape to investigate the network pharmacological effects of B. integerrima on DN. KEGG pathway analysis of core genes exposed their involvement in excess glucose-activated signaling pathway. Then, expression of core genes was validated through machine learning classifiers. Finally, PyRx and AMBER18 software was used for molecular docking and simulation. We found that Armepavine, Berberine, Glaucine, Magnoflorine, Reticuline, Quercetin inhibits the growth of diabetic nephropathy by affecting ICAM1, PRKCB, IKBKB, KDR, ALOX5, VCAM1, SYK, TBXA2R, LCK, and F3 genes. Machine learning revealed SYK and PRKCB as potential genes that could use as diagnostic biomarkers against DN. Furthermore, docking and simulation analysis showed the binding affinity and stability of the active compound with target genes. Our study revealed that B. integerrima has preventive effect on DN by acting on glucose-activated signaling pathways. However, experimental studies are needed to reveal biosafety profiles of B. integerrima in DN.Communicated by Ramaswamy H. Sarma.

Chemical constituents from ethanol extract of Polyalthia rumphii branches and their cytotoxicity evaluation

ABSTRACT Twelve known compounds, including eight alkaloids, three lignans and one gossypol derivative, were isolated from the branches of Polyalthia rumphii (Blume ex Hensch.) Merr., Annonaceae. The chemical structures were determined by spectroscopic methods and comparison with literature data. All the isolates were evaluated the cytotoxicity against three human cancer cell lines: Hela, MCF-7 and A549, the results showed that partial of isolates displayed weak cytotoxicities with the IC50 values ranging from 25 to 40 µg/ml.

Application of OCT angiography in ophthalmology / 国际眼科杂志(Guoji Yanke Zazhi)

Optical coherence tomography angiography (OCTA) is a new technology of angiography in recent years.In addition to the advantages of traditional OCT,it can observe blood flow in different retinal and choroidal segmentation slab.By using the pseudo-color,abnormal vascular structure can be distinguished from normal vascular structure of the retina.Dye injection is not needed with OCTA,which is different from fundus fluorescein angiography (FFA) and indocyanine green angiography (ICGA).OCTA provides more and more accurate blood flow information.However,like other biometric technology,OCTA has its limitations and shortcomings.This review will analyze and summarize the operating principle of OCTA,its application in ophthalmology,as well as its advantages and limitations.