Objective:To investigate the potential of praeruptorin A (PA) in alleviating inflammatory damage in sepsis through the inhibition of ferritin expression.Methods:C57BL/6 mice were intraperitoneally injected with lipopolysaccharide (LPS) to establish the model of sepsis. After 6 and 12 h of PA intervention, serum levels of inflammatory cytokines IL-6 and TNF-α were measured by ELISA. Kidney tissues were collected at 72 h for HE staining to assess inflammatory cell infiltration and tissue damage. Human neutrophils were divided into four groups: control, LPS, ferritin, and LPS+ ferritin groups. After 12 h of intervention, qRT-PCR was used to detect the expression of IL-6 and TNF-α mRNA. In order to observe the effect of PA on the expression of inflammatory cytokines and ferritin, human neutrophils were grouped into control, LPS, and LPS+ PA (2/3/4 μmol/L) groups. After 12 h of intervention, qRT-PCR was performed to measure the expression of IL-1β, IL-6, TNF-α, and ferritin mRNA; ELISA was used to quantify the levels of IL-1β, IL-6, and TNF-α in culture supernatants; Western blot was used to analyze the expression of ferritin. Molecular docking was conducted to verify interactions between PA and ferritin.Results:Significant inflammatory cell recruitment, tissue damage, and elevated serum levels of IL-6 and TNF-α ( P<0.01) were observed in mice with LPS-induced sepsis. PA significantly inhibited cytokine secretion ( P<0.01) and alleviated tissue injury in sepsis mice. In human neutrophil models, ferritin upregulated the expression of IL-6 and TNF-α mRNA ( P<0.01); LPS stimulation alone increased the expression of IL-1β, IL-6, TNF-α, and ferritin at both mRNA and protein levels ( P<0.01), while co-stimulation with PA (3/4 μmol/L) significantly reversed the aforementioned results ( P<0.01). Molecular docking confirmed there were interaction sites between PA and ferritin. Conclusion:PA inhibits the release of inflammatory cytokines and alleviates tissue damage in sepsis, and the potential mechanism may involve modulating ferritin expression to suppress inflammatory responses.

Objective:To investigate the potential of praeruptorin A (PA) in alleviating inflammatory damage in sepsis through the inhibition of ferritin expression.Methods:C57BL/6 mice were intraperitoneally injected with lipopolysaccharide (LPS) to establish the model of sepsis. After 6 and 12 h of PA intervention, serum levels of inflammatory cytokines IL-6 and TNF-α were measured by ELISA. Kidney tissues were collected at 72 h for HE staining to assess inflammatory cell infiltration and tissue damage. Human neutrophils were divided into four groups: control, LPS, ferritin, and LPS+ ferritin groups. After 12 h of intervention, qRT-PCR was used to detect the expression of IL-6 and TNF-α mRNA. In order to observe the effect of PA on the expression of inflammatory cytokines and ferritin, human neutrophils were grouped into control, LPS, and LPS+ PA (2/3/4 μmol/L) groups. After 12 h of intervention, qRT-PCR was performed to measure the expression of IL-1β, IL-6, TNF-α, and ferritin mRNA; ELISA was used to quantify the levels of IL-1β, IL-6, and TNF-α in culture supernatants; Western blot was used to analyze the expression of ferritin. Molecular docking was conducted to verify interactions between PA and ferritin.Results:Significant inflammatory cell recruitment, tissue damage, and elevated serum levels of IL-6 and TNF-α ( P<0.01) were observed in mice with LPS-induced sepsis. PA significantly inhibited cytokine secretion ( P<0.01) and alleviated tissue injury in sepsis mice. In human neutrophil models, ferritin upregulated the expression of IL-6 and TNF-α mRNA ( P<0.01); LPS stimulation alone increased the expression of IL-1β, IL-6, TNF-α, and ferritin at both mRNA and protein levels ( P<0.01), while co-stimulation with PA (3/4 μmol/L) significantly reversed the aforementioned results ( P<0.01). Molecular docking confirmed there were interaction sites between PA and ferritin. Conclusion:PA inhibits the release of inflammatory cytokines and alleviates tissue damage in sepsis, and the potential mechanism may involve modulating ferritin expression to suppress inflammatory responses.

Objective To investigate the characteristics and the clinical significance of relevant parame-ters of blood in psoriasis vulgaris(PV). Methods A retrospective analysis among 38 PV patients and 40 normal controls was done. The comparing parameters contained NLR,CRP,total cholesterol,triglyceride,serum uric acid.Pearson correlation analysis was used to detect the correlations.Results NLR,total cholesterol,triglyceride, serum uric acid in psoriasis vulgaris patients were significantly higher than in the normal controls(P < 0.05). There was a statistically significant correlation between NLR and PASI in the PV patients,but no correlation of CRP with NLR and PASI(P > 0.05). In the patients with PASI ≥ 7,the serum uric acid level was significantly higher than in those with PASI < 7. Conclusions NLR is indicateive of the severity and state of inflammation. The severer PV,the higher the level of serum uric acid.

Objective To compare the value of central venous pressure (CVP) measured by peripherally inserted central catheters (PICC) and centrally inserted central catheters (CICC) in elderly patients with severe diseases.Methods Paired design and self-controlled was applied in the research. CVP was measured by 2 different measurement approaches in patients with PICC and CICC simultaneously. The sample size was calculated by the enumeration method through the accuracy estimation of consistency evaluation of quantitative measurement, and the required number was 70.Results Among the 70 collected samples, the mean values of the measured CVP by PICC and CICC were (7.995±3.435) cmH2O and (7.743±3.277) cmH2O; no statistically significant difference was observed (t=1.622,P=0.109). The pearson's linear correlation coefficient of the CVP measured by 2 different measurement approaches was 0.926 (P<0.0001). A linear regression model through the origin of the CVP measured by 2 different measurement approaches was fitted with the linear regression equation of CVPPICC=1.023 CVPCICC (R2=0.978); and the 95%CI of the prediction line contained the reference line. The Bland-Altman plot showed that 64 samples fell within limits of agreement (LoA), LoA was -2.300-2.804, with a consistent rate of 91.43%. All the plots out of the LoA did not exceeded the 95%CI.Conclusions The CVP measured by CICC and PICC exhibit high consistency. Therefore, PICC can be used to replace the CICC in the CVP monitoring.