As a kind of potent stimulus, lipopolysaccharide (LPS) has the ability to cause cell damage by activating toll-like receptor(TLR)4, then nuclear factor kappa B (NF-κB) translocates into the nucleus and changes the expression of related inflammatory genes. Baicalin is extracted from Radix Scutellariae, which possesses anti-inflammation, antioxidant and antibacterial properties. However, the effects of it on LPS-induced liver inflammation have not been fully elucidated. This study aims to investigate the anti-inflammatory effects of Baicalin on the LPS-induced liver inflammation and its underlying molecular mechanisms in chicken. The results of histopathological changes, serum biochemical analysis, NO levels and myeloperoxidase activity showed that Baicalin pretreatment ameliorated LPS-induced liver inflammation. ELISA and qPCR assays showed that Baicalin dose-dependently suppressed the production of IL-1β, IL-6, and TNF-α. Furthermore, the mRNA expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) were significantly decreased by Baicalin. TLR4 is an important sensor in LPS infection. Molecular studies showed that the expression of TLR4 was inhibited by Baicalin pretreatment. In addition, Baicalin pretreatment inhibited NF-kB signaling pathway activation. All results demonstrated the protective effects of Baicalin pretreatment against LPS-induced liver inflammation in chicken via negative regulation of inflammatory mediators through the down-regulation of TLR4 expression and the inhibition of NF-kB activation.

Hypericum perforatum L., also known as Saint John’s Wort, has been well studied for its chemical composition and pharmacological activity. In this study, the antiviral activities of H. perforatum on infectious bronchitis virus (IBV) were evaluated in vitro and in vivo for the first time. The results of in vitro experiments confirmed that the antiviral component of H. perforatum was ethyl acetate extraction section (HPE), and results showed that treatment with HPE significantly reduced the relative messenger ribonucleic acid (mRNA) expression and virus titer of IBV, and reduced positive green immunofluorescence signal of IBV in chicken embryo kidney (CEK) cells. HPE treatment at doses of 480–120 mg/kg for 5 days, reduced IBV induced injury in the trachea and kidney, moreover, reduced the mRNA expression level of IBV in the trachea and kidney in vivo. The mRNA expression levels of IL-6, tumor necrosis factor alpha (TNF-α), and nuclear factor kappa beta (NF-κB) significantly decreased, but melanoma differentiation-associated protein 5 (MDA5), mitochondrial antiviral signaling gene, interferon alpha (IFN-α), and interferon beta (IFN-β) mRNA levels significantly increased in vitro and in vivo. Our findings demonstrated that HPE had significant anti-IBV effects in vitro and in vivo, respectively. In addition, it is possible owing to up-regulate mRNA expression of type I interferon through the MDA5 signaling pathway and down-regulate mRNA expression of IL-6 and TNF-α via the NF-κB signaling pathway. Moreover, the mainly active compositions of HPE analyzed by high-performance liquid chromatography/electrospray ionization–mass spectroscopy (ESI-MS) are hyperoside, quercitrin, quercetin, pseudohypericin, and hypericin, and a combination of these compounds could mediate the antiviral activities. This might accelerate our understanding of the antiviral effect of H. perforatum and provide new insights into the development of effective therapeutic strategies.

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It is well understood that liver cytochrome p450 enzymes are responsible for AFB1 bioactivation, while phase-II enzymes regulated by the transcription factor nuclear factor-erythroid-2-related factor 2 (Nrf2) are involved in detoxification of AFB1. In this study, we explored the potential of curcumin to prevent AFB1-induced liver injury by modulating liver phase-I and phase-II enzymes along with Nrf2 involved in AFB1 bioactivation and detoxification. Arbor Acres broiler were divided into four groups including control group (G1; fed only basal feed), curcumin alone-treated group (G2; 450 mg/kg feed), AFB1-fed group (G3; 5 mg/kg feed), and curcumin plus AFB1 group (G4; 5 mg AFB1+450 mg curcumin/kg feed). After 28 days, liver and blood samples were collected for different analyses. Histological and phenotypic results revealed that AFB1-induced liver injury was partially ameliorated by curcumin supplementation. Compared to AFB1 alone-treated group, serum biochemical parameters and liver antioxidant status showed that curcumin supplementation significantly prevented AFB1-induced liver injury. RT-PCR and western blot results revealed that curcumin inhibited CYP enzymes-mediated bioactivation of AFB1 at mRNA and protein level. Transcription factor Nrf2, its downstream genes such as GSTA3, and GSTM2 mRNA, and protein expression level significantly upregulated via dietary curcumin. In addition, GSTs enzyme activity was enhanced with dietary curcumin which plays a crucial role in AFB1-detoxification. Conclusively, the study provided a scientific basis for the use of curcumin in broiler’s diet and contributed to explore the multi-target preventive actions of curcumin against AFB1-induced liver injury through the modulation of phase-I and phase-II enzymes, and its potent anti-oxidative effects.

Risk stratification of young patients with hypertension remains challenging. Generally, machine learning (ML) is considered a promising alternative to traditional methods for clinical predictions because it is capable of processing large amounts of complex data. We, therefore, explored the feasibility of an ML approach for predicting outcomes in young patients with hypertension and compared its performance with that of approaches now commonly used in clinical practice. Baseline clinical data and a composite end point—comprising all-cause death, acute myocardial infarction, coronary artery revascularization, new-onset heart failure, new-onset atrial fibrillation/atrial flutter, sustained ventricular tachycardia/ventricular fibrillation, peripheral artery revascularization, new-onset stroke, end-stage renal disease—were evaluated in 508 young patients with hypertension (30.83±6.17 years) who had been treated at a tertiary hospital. Construction of the ML model, which consisted of recursive feature elimination, extreme gradient boosting, and 10-fold cross-validation, was performed at the 33-month follow-up evaluation, and the model’s performance was compared with that of the Cox regression and recalibrated Framingham Risk Score models. An 11-variable combination was considered most valuable for predicting outcomes using the ML approach. The C statistic for identifying patients with composite end points was 0.757 (95% CI, 0.660–0.854) for the ML model, whereas for Cox regression model and the recalibrated Framingham Risk Score model it was 0.723 (95% CI, 0.636–0.810) and 0.529 (95% CI, 0.403–0.655). The ML approach was comparable with Cox regression for determining the clinical prognosis of young patients with hypertension and was better than that of the recalibrated Framingham Risk Score model.