Objective:To investigate the counteractive effect of mouse dermal fibroblasts (MdFBs) during their adipogenic differentiation against Staphylococcus aureus infection, and to explore its mechanisms. Methods:MdFBs were obtained from newborn C57BL/6 mice, and their adipogenic differentiation was induced by culture in an adipogenic medium for 48 hours. Real-time fluorescence-based quantitative PCR (RT-PCR) was performed to determine the mRNA expression of cathelicidin antimicrobial peptide (CAMP) on days 0-6 during the adipogenic differentiation of MdFBs, and Western blot analysis to determine the protein expression of CAMP in the culture supernatant of MdFBs during their adipogenic differentiation. MdFBs were divided into 4 groups: co-stimulation group stimulated by S. aureus suspensions and cultured in an adipogenic medium, adipogenic control group cultured in an adipogenic medium, S. aureus-stimulation group stimulated by S. aureus suspensions and cultured in a common medium, and control group stimulated by phosphate-buffered saline and cultured in a common medium; Western blot analysis and RT-PCR were conducted to determine the protein and mRNA expression of CAMP. S. aureus (5 × 10 4 CFU/ml) was cultured with the culture supernatant of MdFBs after 5-day adipogenic differentiation (adipogenic group), and the growth activity was evaluated every 2 hours during 10 - 24 hours after the start of co-culture; S. aureus cultured with the culture supernatant of MdFBs in a common medium served as the normal control group, and that cultured with cell-free culture supernatant served as the negative control group. Differences between groups were assessed using unpaired t-test or analysis of variance. Results:Significant differences were observed in the relative mRNA expression of CAMP among different time points (days 0, 1, 2, 4, and 6) during the adipogenic differentiation of MdFBs (1.14 ± 0.74, 68.04 ± 12.72, 683.12 ± 38.06, 1 390.68 ± 226.21, 454.57 ± 204.12, F = 50.08, P < 0.001) ; the CAMP mRNA expression was significantly higher on days 1, 2, 4, and 6 than on day 0 ( t = 9.09, 31.03, 10.63, 3.85, respectively, all P < 0.05), and showed an initial rise and subsequent fall during days 0 - 6. The CAMP protein expression in the culture supernatant of MdFBs peaked on days 2-5 and subsequently decreased. Significant differences were observed in the mRNA and protein expression of CAMP among the control group, S. aureus-stimulation group, adipogenic control group and co-stimulation group (mRNA: 0.08 ± 0.02, 0.38 ± 0.10, 0.49 ± 0.11, 0.80 ± 0.03, respectively, F = 43.25, P < 0.05; protein: 0.433 ± 0.176, 0.574 ± 0.176, 1.007 ± 0.176, 1.217 ± 0.176, respectively, F = 46.79, P < 0.05), and the relative mRNA and protein expression of CAMP was significantly higher in the co-stimulation group than in the adipogenic control group, S. aureus-stimulation group and control group (all P < 0.05). At 10 hours during culture, the growth activity of S. aureus was significantly lower in the adipogenic group (0.053 ± 0.015) than in the normal control group and negative control group (0.109 ± 0.015, 0.106 ± 0.015, t = 11.30, 13.26, respectively, both P < 0.05) ; during 10 - 24 hours, the growth activity of S. aureus also showed a significant decrease in the adipogenic group compared with the normal control group and negative control group (all P < 0.05) . Conclusion:MdFBs secreted CAMP during the adipogenic differentiation, and could inhibit the proliferation of S. aureus.

Surface electromyography (sEMG) has been widely used in the study of clinical medicine, rehabilitation medicine, sports, etc., and its endpoints should be detected accurately before analyzing. However, endpoint detection is vulnerable to electrocardiogram (ECG) interference when the sEMG recorders are placed near the heart. In this paper, an endpoint-detection algorithm which is insensitive to ECG interference is proposed. In the algorithm, endpoints of sEMG are detected based on the short-time energy and short-time zero-crossing rates of sEMG. The thresholds of short-time energy and short-time zero-crossing rate are set according to the statistical difference of short-time zero-crossing rate between sEMG and ECG, and the statistical difference of short-time energy between sEMG and the background noise. Experiment results on the sEMG of rectus abdominis muscle demonstrate that the algorithm detects the endpoints of the sEMG with a high accuracy rate of 95.6%.