Mediators of Inflammation最新文献

Background: Electronic devices such as cellphones, microwaves, and other household devices are known to emit electromagnetic waves. As such, it creates an environment that may disrupt homeostasis. Ginsenosides in red ginseng is a Korean herb that is known for their anticancer, anti-inflammatory, and antidiabetic properties. This study aims to assess the therapeutic properties of ginsenosides in extremely low-frequency electromagnetic field exposure (ELF-EMF) environment.

Materials and methods: To observe the anti-inflammatory effects of ginsenosides, lipopolysaccharide (LPS) and ELF-EMF-induced RAW 264.7 cells were treated with 14 ginsenosides. Here, the production and gene expression of pro-inflammatory cytokines such as TNF-α, IL-6, IL-1β, and nitric oxide (NO) were determined. Furthermore, neuronal apoptosis was examined as this may be induced by excessive secretion of pro-inflammatory cytokines and increased calcium influx.

Results: RAW264.7 cells exposed to ELF-EMF showed an increase in NO production and pro-inflammatory cytokines. Moreover, under ELF-EMF exposure, translocation of NF-kB increased and NFAT2, due to elevated calcium influx, increased as well. These inflammatory responses were alleviated by the ginsenosides and among the 14 ginsenosides, ginsenoside Rd had the most potent anti-inflammatory effect.

Conclusion: Ginsenosides alleviate inflammation induced by ELF-EMF by downregulating inflammatory-related cytokines and proteins. It also had an effect on decreasing nerve cell apoptosis by reducing inflammatory response.

Background: Infection is a pathogenetic factor for bronchopulmonary dysplasia (BPD), and corticosteroids are often used for its prevention or treatment. However, few studies have examined their combined effects on brain injury in the context of infection.

Methods: Rat pups received lipopolysaccharide (LPS) on postnatal Day 1 (P1), followed by tapering doses of dexamethasone (Dex) or hydrocortisone (HC) from P2 to P4. We measured body and brain weights, TUNEL-positive cell counts, synaptic protein levels, and mRNA expression of glucocorticoid receptor (GR) and mineralocorticoid receptor (MR) in six brain regions at P5.

Results: The LPS-HC and LPS-Dex groups showed more TUNEL-positive cells in the hippocampus, cerebellum, and brain stem compared to LPS-naïve controls. Oligodendrocyte precursor cells were the predominant TUNEL-positive cells in the hippocampus and brain stem. Additionally, the LPS-Dex or LPS-HC group showed significantly reduced levels of postsynaptic density protein 95 (PSD95), a postsynaptic protein, in these regions, while treatment with Dex or HC alone did not impact PSD95 expression. GR mRNA was significantly reduced in cortex, striatum, hippocampus, and cerebellum in LPS-HC group, with MR mRNA reduction limited primarily to the striatum.

Conclusions: LPS sensitized the immature brain to Dex or HC-related cell death to possible apoptosis and augmented the LPS-induced disruption of synaptic integrity in certain brain regions, potentially via altered GR and MR expression that may modulate corticosteroid receptor signaling.

Intervertebral disk degeneration (IVDD) usually causes lower back pain (LBP). Mechanical stress, trauma, aseptic inflammation, infection, and genetic susceptibility can accelerate the development of IVDD. Reportedly, proinflammatory cytokines and extracellular matrix (ECM) degradation play significant roles in IVDD progression. Therefore, anti-inflammatory treatments and ECM inhibition can potentially delay the progression of IVDD. Velutin, a natural flavonoid, has the vigorous effects of suppressing inflammation. In this study, we researched the protective effects of velutin and the underlying mechanisms. Additionally, we evaluated its validity in a mouse IVDD model. The results indicated that velutin effectively suppressed interleukin-1β-induced inflammatory mediators. Moreover, our findings revealed the mechanisms of velutin's anti-inflammatory effects. Our results indicate that velutin is a potential therapeutic agent for IVDD.

Sterile inflammation (SI) is an inflammatory response triggered by the release of damage-associated molecular patterns (DAMPs) from dying cells, distinct from normal inflammation in its origin from tissue injury and necrosis rather than microbial invasion. Circulating nucleic acids (CNAs), high-mobility group box 1 (HMGB1), von Willebrand factor (vWF), and S100b protein are notable markers of SI, indicative of tissue damage and implicated in thrombotic disorders. Innate immunity, involving cells like macrophages and dendritic cells, recognizes DAMPs via pattern recognition receptors (PRRs) like Toll-like receptors and NOD-like receptors, initiating inflammatory signaling cascades central to SI and its cardiovascular consequences. Thrombosis, a common outcome of SI, underscores the intricate interplay between inflammation and hemostasis, with hypoxia exacerbating thrombotic risk through platelet activation and endothelial dysfunction. The established link between inflammation and thrombosis highlights the clinical significance of SI, where molecules like HMGB1, extracellular RNA (eRNA), and eDNA actively participate in thromboembolic disorders. SI's relevance is particularly evident in COVID-19-induced thrombotic disorders, where dysregulated immune responses and endothelial dysfunction contribute to systemic inflammation and heightened thrombotic risk. Understanding SI's mechanisms in these contexts is vital for developing targeted therapies to mitigate vascular complications and enhance patient outcomes in cardiovascular diseases and COVID-19-associated thrombosis.

Background: Aging is a multifaceted physiological process characterized by progressive multiorgan dysfunction, oxidative stress, neuronal injury, cognitive impairment, and alterations in gut microbiota composition. Licorice, a widely used traditional medicinal herb, contains diverse bioactive constituents; however, its overall antiaging properties and mechanistic basis in aging models have not been systematically elucidated.

Methods: Aging mice model was established using D-galactose (D-Gal). Body weight, organ indices, senescence markers, antioxidant activity, neuronal integrity, and behavioral performance were assessed to evaluate the protective role of licorice water (LW) extract. Further, gut microbiota profiling, network pharmacology, and western blotting were employed to investigate further the potential mechanisms underlying the antiaging effects of LW.

Results: LW administration significantly improved body weight gain, organ indices, and hippocampal structure in aging mice, increased antioxidant enzyme activity, and decreased the proportion of SA-β-Gal-positive cells. Moreover, LW treatment reshaped gut microbiota composition by lowering the Firmicutes/Bacteroidota (F/B) ratio and increasing the relative abundance of beneficial bacterial taxa. Network pharmacology analysis identified 66 licorice-associated antiaging genes, with quercetin, kaempferol, naringenin, formononetin, and licochalcone A as key active components. The principal molecular targets included AKT1, TP53, ESR1, CASPASE3, and BCL2, while the major enriched pathways involved PI3K-Akt, lipid and atherosclerosis, AGE-RAGE, MAPK, and IL-17 pathway. Furthermore, Western blot analysis revealed that LW significantly downregulated the expression of p-PI3K, p-AKT, and p-mTOR in brain tissue.

Conclusion: These findings demonstrate that LW exerts protective antiaging effects in D-Gal-induced mice by enhancing antioxidant activities, safeguarding neuronal function to improve cognition, restoring gut microbiota balance, and modulating the PI3K/AKT/mTOR pathway, supporting its promise as a candidate for antiaging interventions.

Sepsis-induced myocardial injury (SIMI) greatly increases the mortality rate of sepsis. Although paeoniflorin (PF) has been proven to improve survival in sepsis, the detailed mechanism of PF on SIMI remains elusive. In this study, network pharmacology revealed 90 overlapping targets between PF- and SIMI-related targets. Analysis using the molecular complex detection (MCODE) method identified a significant module with scores exceeding 30, comprising the top 10 targets: Akt1, STAT3, CASP3, BCL2, TP53, PTGS2, CXCL8, TLR4, CCL2, and ICAM1. These targets are involved in tissue repair during inflammatory response, apoptosis, immunity, and lipopolysaccharide (LPS) immune receptor activity. The enriched pathways in inflammatory signaling, include NF-κB signaling pathway, HIF-1 signaling pathway, MAPK signaling pathway, and PI3K-Akt signaling pathway. Molecular docking further verified the strong binding abilities of PF to PI3K, Akt1, ERK1, ERK2, HIF-1α, TLR4, and NF-κB. In LPS-induced sepsis rat model, PF pretreatment inhibited PI3K/Akt/ERK-mediated HIF-1α and TLR4/MyD88/NF-κB signaling, thereby reducing inflammation by decreasing the levels of tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) in serum and cardiac tissue. Ultimately, PF ameliorated SIMI by improving cardiac pathological and functional changes and mitigating myocardial injury markers, such as lactate dehydrogenase (LDH), CK-MB, cTnT/TNNT2, TNNI3/cTn-I, and aspartate aminotransferase (AST). Collectively, the PI3K/Akt/ERK-mediated HIF-1α and TLR4/MyD88/NF-κB inflammation signaling appear to be the primary mechanisms through which PF exerts its beneficial effects on SIMI.

Objective: This study aimed to investigate the impact of new inflammation/nutrition-based indicators-the modified cachexia index (mCXI) on the prognosis of elderly patients with colorectal cancer and develop a nomogram model.

Methods: A retrospective analysis was conducted using clinical data from patients over 70 years old diagnosed with colorectal cancer, at the Affiliated Hospital of Qingdao University between July 2018 and December 2023. Univariate and multivariate Cox regression analyses, based on overall survival (OS) and recurrence-free survival (RFS), identified independent prognostic factors. A nomogram prediction model was constructed using multivariate analysis.

Results: The study included 456 patients, comprising 273 males (59.9%) and 183 females (40.1%), with a mean age of 75 years. The median follow-up was 41 months. The 1-, 3-, and 5-year OS rates were 85%, 65%, and 50%, respectively, while the 1-, 3-, and 5-year RFS rates were 80%, 55%, and 40%, respectively. Multivariate Cox regression identified age, tumor T stage, tumor N stage, and mCXI as independent factors affecting both OS and RFS. A nomogram prognostic model was developed, with area under the ROC curve (AUC) values of 0.742, 0.809, and 0.799 for 1-, 3-, and 5-year OS, respectively, and AUC values of 0.769, 0.798, and 0.797 for 1-, 3-, and 5-year RFS, respectively. Calibration curves indicated strong agreement with the ideal model and decision curve analysis confirmed the model's robust predictive accuracy.

Conclusion: The mCXI serves as an independent risk factor for both RFS and OS in elderly patients with colorectal cancer. The nomogram prediction model demonstrates strong prognostic value for this patient group.

The detachment of cardiogenic emboli, the formation of arterial thrombosis, and the use of tourniquets in emergency situations of massive hemorrhage can all lead to acute limb ischemia. In order to save the limb, blood flow must be rapidly restored. However, the resulting ischemia reperfusion (IR) injury may trigger systemic inflammatory responses of varying degrees, and cause damage to distant organs. Acute lung injury (ALI) caused by acute limb IR (LIR) can significantly affect the prognosis of patients. Despite a large number of previous studies, there is currently no specific exists for this condition. This study aims to investigate the potential benefits of lutein on ALI caused by LIR (LIR-ALI). Network pharmacology analysis was used to predict the key targets and signaling pathways of lutein in the treatment of ALI. In addition, we established a mice model of LIR-ALI. Histological, ELISA, and Western blotting analyses were performed to determine the therapeutic effects and potential mechanisms of action. Our study found that lutein dose-dependently mitigated lung oxidative stress, inflammatory cell infiltration, and pyroptosis-related protein expression induced by LIR. The protective effect is partially mediated by regulating the PPAR-γ/PI3K-AKT/NLRP3 pathway to inhibit pyroptosis.

Background: Lung cancer oncogenesis involves interactions between immune cells and inflammatory cytokines. However, their causal relationships and mediating mechanism remain unclear.

Methods: Using a mediating Mendelian randomization (MR) approach, we analyzed genome-wide association study (GWAS) data for 731 immune-cellular phenotypes, 41 cytokines, and eight related lung cancer phenotypes.

Results: BAFF-R expression in IgD⁺ CD24⁺ B cells was positively associated with lung adenocarcinoma (LUAD) risk (odds ratio [OR], 1.0168 [95% confidence interval [CI], 1.0006-1.0332]), mediated by macrophage migration inhibition factor (MIF) with a mediation proportion of 14.2% (95% CI, 0.00007-0.0046). CD39 expression on secreting CD4 Tregs was related to an increased risk of small-cell lung cancer (SCLC) (OR, 1.0306 [95% CI, 1.0006-1.0616]), mediated by interleukin (IL)-2 and IL-6 with mediation proportions of 8.43% (95% CI, 0.00005-0.005) and 5.1% (95% CI, 0.00006-0.003), respectively. CD28 expression on CD39⁺ CD4⁺ T cells was positively correlated to lung squamous cell carcinoma (LUSC) risk (OR, 1.0335 [95% CI, 1.009-1.0586]), inversely mediated by IL-16 (95% CI, -0.01 to -0.0003).

Conclusions: These findings reveal the associations between immune cells, inflammatory cytokines, and lung cancer risk, providing insights into cancer diagnosis and treatment.

Background: This study focused on utilizing machine learning techniques to construct a predictive nomograph for early identification of acute pancreatitis (AP) patients at risk of developing acute respiratory distress syndrome (ARDS).

Methods: We retrospectively analyzed 427 AP patients from Tongji Hospital (2010-2021) and externally validated the model using the MIMIC-IV database. Six machine learning algorithms were compared, with the support vector machine (SVM) selected for nomogram construction. Key predictors included age, sex, SOFA score, C-reactive protein (CRP), platelet count (PLT), total bilirubin (TBIL), and direct bilirubin (DBIL). Model performance was assessed via area under the curve (AUC), calibration curves, and decision curve analysis (DCA).

Results: The SVM model exhibited the best performance among six machine-learning models assessed. Key predictors including age, sex, SOFA, CRP, PLT, TBIL, and DBIL levels were incorporated into the nomogram. The nomogram demonstrated good discriminatory ability and clinical applicability, with a C-index of 0.818 in the training cohort and 0.799 in the testing cohort. External validation using the MIMIC IV database further confirmed its accuracy, with a C-index of 0.759. Notably, calibration curves showed excellent agreement between predicted and observed outcomes, and DCA indicated a favorable net benefit, reinforcing the model's reliability.

Conclusions: The prediction nomogram constructed based on the SVM model in this study can effectively predict the probability of AP complicated by ARDS.