Mechanism of action of Coptidis Rhizome in treating periodontitis based on network pharmacology and in vitro validation.

OBJECTIVE: Explore the therapeutic mechanism of Coptidis Rhizome (CR) in periodontitis using network pharmacology, and validate it through molecular docking and in vitro experiments. METHODS: Screened potential active components and target genes of CR from TCMSP and Swiss databases. Identified periodontitis-related target genes using GeneCards. Found common target genes using Venny. Conducted GO and KEGG pathway analysis. Performed molecular docking and in vitro experiments using Berberine, the main active component of CR, on lymphocytes from healthy and periodontitis patients. Assessed effects on inflammatory factors using CCK-8, flow cytometry, and ELISA. RESULTS: Fourteen active components and 291 targets of CR were identified. 30 intersecting target genes with periodontitis were found. GO and KEGG analysis revealed oxidative stress response and IL-17 signaling pathway as key mechanisms. Molecular docking showed strong binding of Berberine with ALOX5, AKT1, NOS2, and TNF. In vitro experiments have demonstrated the ability of berberine to inhibit the expression of Th17 + and other immune related cells in LPS stimulated lymphocytes, and reduce the secretion of IL-6, IL-8, and IL-17. CONCLUSION: CR treats periodontitis through a multi-component, multi-target, and multi-pathway approach. Berberine, its key component, acts through the IL-17 signaling pathway to exert anti-inflammatory effects.

The associations of two novel inflammation indexes, systemic immune-inflammation index (SII) and system inflammation response index (SIRI), with periodontitis: evidence from NHANES 2009-2014.

OBJECTIVES: The research's goal is to look for any potential relationships between the systemic immune-inflammation index (SII) and the system inflammation response index (SIRI), along with inflammation indicators and the likelihood of periodontitis. METHODS: Ten thousand two hundred eighty-two individuals in sum were determined to be eligible for this cross-sectional study from the National Health and Nutrition Examination Survey (NHANES) between 2009 and 2014. Multiple logistic regression, generalized additive model, smooth curve fitting, subgroup analysis, and interaction tests were done for analyzing the association between periodontitis and SII, SIRI, and other inflammatory indicators. RESULTS: The analysis, adjusted for population weighting, revealed that individuals with moderate/severe periodontitis had SII levels of 545.46 (95% CI (529.10, 561.82), P = 0.0044) and SIRI levels of 1.33 (95% CI (1.29, 1.37), P < 0.0001). In a fully adjusted multivariate logistic regression model, SII was not sensibly associated with moderate/severe periodontitis among the continuous and quartile Q1-Q4 groups (OR = 0.97, 95% CI (0.91, 1.02)). The continuous variable of SIRI (OR = 1.11, 95% CI (1.06, 1.17)) and the quartile Q4 group (OR = 1.58, 95% CI (1.28, 1.94)) had a deemed significant positive association with moderate to severe periodontitis. In addition, other inflammatory indicators, especially NLR, PPN, PLR, MLR, PC, NC, and MC were observed to be notably involved moderate/severe periodontist in this research. CONCLUSION: We explored the association between periodontitis and two novel comprehensive markers of inflammation (SII and SIRI). CLINICAL RELEVANCE: These inflammatory markers are expected to serve as tools to assist clinicians in diagnosing periodontitis.

A New Hyperchaotic 4D-FDHNN System with Four Positive Lyapunov Exponents and Its Application in Image Encryption.

In this paper, a hyperchaotic four-dimensional fractional discrete Hopfield neural network system (4D-FDHNN) with four positive Lyapunov exponents is proposed. Firstly, the chaotic dynamics' characteristics of the system are verified by analyzing and comparing the iterative trajectory diagram, phase diagram, attractor diagram, 0-1 test, sample entropy, and Lyapunov exponent. Furthermore, a novel image encryption scheme is designed to use the chaotic system as a pseudo-random number generator. In the scenario, the confusion phase using the fractal idea proposes a fractal-like model scrambling method, effectively enhancing the complexity and security of the confusion. For the advanced diffusion phase, we proposed a kind of Hilbert dynamic random diffusion method, synchronously changing the size and location of the pixel values, which improves the efficiency of the encryption algorithm. Finally, simulation results and security analysis experiments show that the proposed encryption algorithm has good efficiency and high security, and can resist common types of attacks.

Synergistic Optimization Strategy Involving Sandwich-like MnO2@rGO and Laponite-Modified PAM for High-Performance Zinc-Ion Batteries and Zinc Dendrite Suppression.

Optimization of the cathode structure and exploration of a novel electrolyte system are important approaches for achieving high-performance zinc-ion batteries (ZIBs) and zinc dendrite suppression. Herein, a quasi-solid-state ZIB combining a sandwich-like MnO2@rGO cathode, a laponite (Lap)-modified polyacrylamide (PAM) hydrogel electrolyte, and an electrodeposited zinc anode is designed and constructed by a synergistic optimization strategy. The MnO2 composite prepared through the intercalation of rGO shows developed mesopores, providing accessible ion transport channels and exhibiting a high electrical conductivity. Thanks to the high dispersion of Lap nanoplates in the hydrogel and good charge-averaging effect, the Zn//PAM-5%Lap//Zn symmetrical battery exhibits a consistent low-voltage polarization of less than 60 mV within 2000 h without a short-circuit phenomenon or any over-potential rise, indicating a stable zinc peeling/plating process. The optimized quasi-solid-state ZIB delivers a high reversible capacity of 291 mA h g-1 at a current density of 0.2 A g-1 due to the synergistic effect of each component of ZIB. Even at a high rate of 2 A g-1, it still maintains a high reversible capacity of 97 mA h g-1 after 2000 cycles, indicating its excellent electrochemical performance. Furthermore, the assembled flexible battery performs excellently in terms of damage and bending resistance.

A SnOx Quantum Dots Embedded Carbon Nanocage Network with Ultrahigh Li Storage Capacity.

Tin-based materials with high specific capacity have been studied as high-performance anodes for energy storage devices. Herein, a SnOx (x = 0, 1, 2) quantum dots@carbon hybrid is designed and prepared by a binary oxide-induced surface-targeted coating of ZIF-8 followed by pyrolysis approach, in which SnOx quantum dots (under 5 nm) are dispersed uniformly throughout the nitrogen-containing carbon nanocage. Each nanocage is cross-linked to form a highly conductive framework. The resulting SnOx@C hybrid exhibits a large BET surface area of 598 m2 g-1, high electrical conductivity, and excellent ion diffusion rate. When applied to LIBs, the SnOx@C reveals an ultrahigh reversible capacity of 1824 mAh g-1 at a current density of 0.2 A g-1, and superior capacities of 1408 and 850 mAh g-1 even at high rates of 2 and 5 A g-1, respectively. The full cell assembled using LiFePO4 as cathode exhibits the high energy density and power density of 335 Wh kg-1 and 575 W kg-1 at 1 C based on the total active mass of cathode and anode. Combined with in situ XRD analysis, the superior electrochemical performance can be attributed to the SnOx-ZnO-C asynchronous and united lithium storage mechanism, which is formed by the well-designed multifeatured construction composed of SnOx quantum dots, interconnected carbon network, and uniformly dispersed ZnO nanoparticles. Importantly, this designed synthesis can be extended for the fabrication of other electrode materials by simply changing the binary oxide precursor to obtain the desired active component or modulating the type of MOFs coating to achieve high-performance LIBs.