Chronic stress accelerates ligature-induced periodontitis by suppressing glucocorticoid receptor-α signaling.

Periodontitis is a common chronic inflammatory disease. Recent studies have shown that chronic stress (CS) might modulate periodontal disease, but there are few models of CS-induced periodontitis, and the underlying mechanisms are unclear. The present study established a rat model of periodontitis associated with CS induced by nylon thread ligatures.

Expression patterns of sarcomeric α-actin, α-actinin and UCP2 in the myocardium of Kunming mice after exposure to c-terminal polypeptide of cardiotrophin-1.

Cardiotrophin-1 (CT-1) activates a distinct form of cardiac muscle cell hypertrophy in which the sarcomeric units are assembled in series. The aim of the study was to determine the expression pattern of sarcomeric contractile protein α-actin, specialized cytoskeletal protein α-actinin and mitochondrial uncoupling protein-2 (UCP2) in myocardial remodeling induced by chronic exposure to CT-1. Kunming mice were intraperitoneally injected with carboxy-terminal polypeptide (CP) of CT-1 (CT-1-CP, 500 μg·kg(-1)· day(-1)) for 1, 2, 3 and 4 week (s), respectively (4 groups obtained according to the injection time, n=10 each, with 5 males and 5 females in each group).

Chronic stress enhances progression of periodontitis via α1-adrenergic signaling: a potential target for periodontal disease therapy.

This study assessed the roles of chronic stress (CS) in the stimulation of the sympathetic nervous system and explored the underlying mechanisms of periodontitis. Using an animal model of periodontitis and CS, the expression of tyrosine hydroxylase (TH) and the protein levels of the α1-adrenergic receptor (α1-AR) and β2-adrenergic receptor (β2-AR) were assessed. Furthermore, human periodontal ligament fibroblasts (HPDLFs) were stimulated with lipopolysaccharide (LPS) to mimic the process of inflammation.

[Analysis of the EEG information of rats epileptic model using unstable periodic orbits].

In order to further research into the EEG information of rats epileptic model, we applied different nonlinear dynamic methods. After having analyzed the EEG signal of rat falling sickness by means of approximate entropy and correlation dimension, we adopted a the new method, unstable periodic orbits, which was used to analyze complex activity of neurons system to look for the change regularity of change in the EEG signal in the whole course of rat's falling sickness. We found period 1 orbits and period 2 orbits to be statistically significant in the data of ictal time of epilepsy.

[Nonlinear analysis on the EEG information of rat epileptic model].

The aim of this study was to develop a new method of epileptic prediction using nonlinear dynamic theory. When rat was falling sickness, its EEG was researched by using approximate entropy and correlation dimension. The results showed the approximate entropy and correlation dimension during epileptic seizure are obviously lower than those before seizure and after seizure.