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Using Preteomic Profiling to Predict Premature Birth

Filed in archive Diagnostics, Methodologies and Instrumentation , Genomics, Proteomics and Bioinformatics on February 12, 2007

Using Preteomic Profiling to Predict Premature Birth
Scientists have identified a proteomics-based method to predict the risks of pre-term childbirth due to amniotic fluid inflammation. A profile based on the presence of human neutrophil defensin 1, human neutrophil defensin 2, calgranulin C and calgranulin A make up an MR score.
The research team analyzed and generated MR scores for amniotic fluid taken from 123 women admitted to the Labor and Birth Unit or the prenatal units at Yale-New Haven Hospital. They found a Direct relationship between the degree of amniotic fluid inflammation as indicated by the MR score, and the severity of infection in the placenta and umbilical cord.

The researchers suggest that these proteomic profile may be used as a tool for the early recognition, diagnosis and treatment of neonatal infections.

Source: Yale

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Tags: pregnancy  proteomics  bioinformatics  diagnostics  childbirth  premature  biotech  using+preteomic 

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