Fibrinogen-like protein 2 deficiency inhibits virus-induced fulminant hepatitis through abrogating inflammatory macrophage activation.

BACKGROUND: Heterogeneous macrophages play an important role in multiple liver diseases, including viral fulminant hepatitis (VFH). Fibrinogen-like protein 2 (FGL2) is expressed on macrophages and regulates VFH pathogenesis; however, the underlying mechanism remains unclear. AIM: To explore how FGL2 regulates macrophage function and subsequent liver injury during VFH. METHODS: Murine hepatitis virus strain 3 (MHV-3) was used to induce VFH in FGL2-deficient (Fgl2-/-) and wild-type (WT) mice. The dynamic constitution of hepatic macrophages was examined. Adoptive transfer of Fgl2-/- or WT bone marrow-derived macrophages (BMDMs) into WT recipients with macrophages depleted prior to infection was carried out and the consequent degree of liver damage was compared. The signaling cascades that may be regulated by FGL2 were detected in macrophages. RESULTS: Following MHV-3 infection, hepatic macrophages were largely replenished by proinflammatory monocyte-derived macrophages (MoMFs), which expressed high levels of FGL2. In Fgl2-/- mice, the number of infiltrating inflammatory MoMFs was reduced compared with that in WT mice after viral infection. Macrophage depletion ameliorated liver damage in WT mice and further alleviated liver damage in Fgl2-/- mice. Adoptive transfer of Fgl2-/- BMDMs into macrophage-removed recipients significantly reduced the degree of liver damage. Inhibition of monocyte infiltration also significantly ameliorated liver damage. Functionally, Fgl2 deletion impaired macrophage phagocytosis and the antigen presentation potential and attenuated the proinflammatory phenotype. At the molecular level, FGL2 deficiency impaired IRF3, IRF7, and p38 phosphorylation, along with NF-κB activation in BMDMs in response to viral infection. CONCLUSION: Infiltrated MoMFs represent a major source of hepatic inflammation during VFH progression, and FGL2 expression on MoMFs maintains the proinflammatory phenotype via p38-dependent positive feedback, contributing to VFH pathogenesis.

[Rapid determination of hypoglycemic tablets by handheld Raman spectrometer and KPCA-clustering analysis].

In the present paper, five different kinds of hypoglycemic tablets were identified using kernel principal component analysis (KPCA)-clustering analysis of their Raman spectra. KPCA was used to compress thousands of spectral data into several variables and to describe the body of the spectra before clustering analysis was chosen as further research method. The results showed that hypoglycemic tablets could be quickly classified using KPCA-clustering analysis. A disadvantage of Raman spectroscopy for this type of analysis is that it is primarily a surface technique. As a consequence, the spectra of the tablet core and its coating might differ. However, the KPCA-clustering analysis turned out to be a sufficiently reliable discrimination, i. e., 96% of the hypoglycemic tablets with coating and 100% of the hypoglycemic tablets without coating were predicted correctly. Overall, the Raman spectroscopic method in the present paper plays a good role in the identification and offers a new approach to the rapid discrimination of different kinds of hypoglycemic tablets.

[Discriminating and quantifying potential adulteration in virgin olive oil by near infrared spectroscopy with BP-ANN and PLS].

In the present paper, the use of near infrared spectroscopy (NIR) as a rapid and cost-effective classification and quantification techniques for the authentication of virgin olive oil were preliminarily investigated. NIR spectra in the range of 12 000 - 3 700 cm(-1) were recorded for pure virgin olive oil and virgin olive oil samples adulterated with varying concentrations of sesame oil, soybean oil and sunflower oil (5%-50% adulterations in the weight of virgin olive oil). The spectral range from 12 000 to 5 390 cm(-1) was adopted to set up an analysis model. In order to handle these data efficiently, after pretreatment, firstly, principal component analysis (PCA) was used to compress thousands of spectral data into several variables and to describe the body of the spectra, and the analysis suggested that the cumulate reliabilities of the first six components was more than 99.999%. Then ANN-BP was chosen as further research method. The six components were secondly applied as ANN-BP inputs. The experiment took a total of 100 samples as original model examples and left 52 samples as unknown samples to predict. Finally, the results showed that the 52 test samples were discriminated accurately. And the calibration models of quantitative analysis were built using partial-least-square (PLS). The R values for PLS model are 98.77, 99.37 and 99.44 for sesame oil, soybean oil and sunflower oil respectively, the root mean standard errors of cross validation (RMSECV) are 1.3, 1.1 and 1.04 respectively. Overall, the near infrared spectroscopic method in the present paper played a good role in the discrimination and quantification, and offered a new approach to the rapid discrimination of pure and adulterated virgin olive oil.