Anti-EMD monoclonal antibody, clone FQS22170

Enamel matrix derivatives (EMDs)-based periodontal tissue regenerative therapy is known to promote healing with minimal inflammatory response after periodontal surgery, i. e., it promotes wound healing with reduced pain and swelling. It has also been reported that macrophages stimulated with amelogenin, a major component of EMD, produce various anti-inflammatory cytokines and growth factors. We previously found that stimulation of monocytes with murine recombinant M180 (rM180) amelogenin suppresses major histocompatibility complex class II (MHC II) gene expression using microarray analysis. However, the detailed molecular mechanisms for this process remain unclear. In the present study, we demonstrated that rM180 amelogenin selectively downmodulates the interferon gamma (IFN gamma)-induced cell surface expression of MHC II molecules in macrophages and this mechanism mediated by rM180 appeared to be widely conserved across species. Furthermore, rM180 accumulated in the nucleus of macrophages at 15 min after stimulation and inhibited the protein expression of class II transactivator (CIITA) which controls the transcription of MHC II by IFN gamma. In addition, reduced MHC II expression on macrophages pretreated with rM180 impaired the expression of T cell activation markers CD25 and CD69, T cell proliferation ability, and IL-2 production by allogenic CD4(+) T lymphocytes in mixed lymphocyte reaction assay. The chromatin immunoprecipitation assay showed that IFN gamma stimulation increased the acetylation of histone H3 lysine 27, which is important for conversion to euchromatin, as well as the trimethylation of histone H3 lysine 4 levels in the CIITA promoter IV (p-IV) region, but both were suppressed in the group stimulated with IFN gamma after rM180 treatment. In conclusion, the present study shows that amelogenin suppresses MHC II expression by altering chromatin structure and inhibiting CIITA p-IV transcription activity, and attenuates subsequent T cell activation. Clinically observed acceleration of wound healing after periodontal surgery by amelogenin may be partially mediated by the mechanism elucidated in this study. In addition, the use of recombinant amelogenin is safe because it is biologically derived protein. Therefore, amelogenin may also be used in future as an immunosuppressant with minimal side effects for organ transplantation or MHC II-linked autoimmune diseases such as type I diabetes, multiple sclerosis, and rheumatoid arthritis, among others.

This study investigates the relationship between particulate matter that have an aerodynamic diameter less than 10 diameter (PM10) and air temperature (T) in the Caribbean basin. To conduct this analysis, eleven years of daily time series recorded in Guadeloupe archipelago were used. Firstly, the stationarity threshold of both time series is quantified using the infinite moving average. Then, statistical analyses were performed using the conditional mean and the joint probability density function method. Both methods used showed a dependence between PM10 and T particularly during the high dust season, i.e. from May to September. From a dynamical point of view, the coherence function highlighted a global correlation information between PM10 and T in the frequency domain. To capture possible localized correlation information, both time series are studied in a multiscale way using a new cross-correlation technique classically based on Empirical Mode Decomposition (EMD) termed the Time-Dependent Intrinsic Correlation (TDIC) analysis. After computing EMD and Ensemble Empirical Mode Decomposition (EEMD) methods, a mode-mixing problem is detected in EMD frame. Consequently, for the first time in air pollution field, a combination of EEMD and TDIC is performed. The achieved results show that the strength and nature of association between PM10 and T vary with time scales and time spells. We found that PM10 from African and marine aerosols are strongly correlated to T respectively for large and small periodicities. One also observed that extreme weather events such as heavy rainfall, hurricanes or drought induce a strong anti-correlation.