Antibacterial effects and microarray-based molecular mechanisms of trans-cinnamaldehyde against Porphyromonas gingivalis.

Porphyromonas gingivalis (P. gingivalis) is one of the keystone pathogenic bacteria of periodontitis and peri-implantitis. This study aimed to investigate the antibacterial effects and molecular mechanisms of trans-cinnamaldehyde (TC), a safe extract from natural plants, on P. gingivalis. Minimum inhibitory and minimum bactericidal concentrations (MIC and MBC) of TC were determined, and scanning and transmission electron microscopies were used to assess the morphological changes. The overall biomass was estimated, and the metabolic activity of biofilms was determined at different TC concentrations. A microarray-based bioinformatics analysis was performed to elucidate the underlying molecular mechanisms of TC-inhibited P. gingivalis, and significant differences among groups were determined. TC showed an inhibitory effect on the proliferation and survival of planktonic P. gingivalis, of which the MIC and MBC were 39.07 µg/mL and 78.13 µg/mL, respectively. TC also significantly suppressed the formation and metabolic activity of P. gingivalis biofilm. The results of the significant pathways and gene ontology (GO) analyses revealed that TC treatment inhibited two metabolic pathways, accompanied by the downregulation of relative genes of nitrogen metabolism (NrfA, NrfH, and PG_2213) and starch and sucrose metabolism (PG_1681, PG_1682, and PG_1683). Thus, this study confirmed TC to be a natural antimicrobial agent against P. gingivalis and further demonstrated that TC suppressed the microbial activity on P. gingivalis through the disruption of physiological metabolism, which might inhibit the growth and the biofilm formation of P. gingivalis.

Liver-Inspired Polyetherketoneketone Scaffolds Simulate Regenerative Signals and Mobilize Anti-Inflammatory Reserves to Reprogram Macrophage Metabolism for Boosted Osteoporotic Osseointegration.

Tissue regeneration is regulated by morphological clues of implants in bone defect repair. Engineered morphology can boost regenerative biocascades that conquer challenges such as material bioinertness and pathological microenvironments. Herein, a correlation between the liver extracellular skeleton morphology and the regenerative signaling, namely hepatocyte growth factor receptor (MET), is found to explain the mystery of rapid liver regeneration. Inspired by this unique structure, a biomimetic morphology is prepared on polyetherketoneketone (PEKK) via femtosecond laser etching and sulfonation. The morphology reproduces MET signaling in macrophages, causing positive immunoregulation and optimized osteogenesis. Moreover, the morphological clue activates an anti-inflammatory reserve (arginase-2) to translocate retrogradely from mitochondria to the cytoplasm due to the difference in spatial binding of heat shock protein 70. This translocation enhances oxidative respiration and complex II activity, reprogramming the metabolism of energy and arginine. The importance of MET signaling and arginase-2 in the anti-inflammatory repair of biomimetic scaffolds is also verified via chemical inhibition and gene knockout. Altogether, this study not only provides a novel biomimetic scaffold for osteoporotic bone defect repair that can simulate regenerative signals, but also reveals the significance and feasibility of strategies to mobilize anti-inflammatory reserves in bone regeneration.

Auxiliary Screening COVID-19 by Serology.

Background: The 2019 novel coronavirus (COVID-19) pandemic remains rampant in many countries/regions. Improving the positive detection rate of COVID-19 infection is an important measure for control and prevention of this pandemic. This meta-analysis aims to systematically summarize the current characteristics of the auxiliary screening methods by serology for COVID-19 infection in real world. Methods: Web of Science, Cochrane Library, Embase, PubMed, CNKI, and Wangfang databases were searched for relevant articles published prior to May 1st, 2022. Data on specificity, sensitivity, positive/negative likelihood ratio, area under curve (AUC), and diagnostic odds ratio (dOR) were calculated purposefully. Results: Sixty-two studies were included with 35,775 participants in the meta-analysis. Among these studies, the pooled estimates for area under the summary receiver operator characteristic of IgG and IgM to predicting COVID-19 diagnosis were 0.974 and 0.928, respectively. The IgG dOR was 209.78 (95% CI: 106.12 to 414.67). The IgM dOR was 78.17 (95% CI: 36.76 to 166.25). Conclusion: Our findings support serum-specific antibody detection may be the main auxiliary screening methods for COVID-19 infection in real world.