Background

The electrical activity of the uterine muscle is representative of uterine contractility. Its characterization may be used to detect a potential risk of preterm delivery in women, even at an early gestational stage.

Methods

We have investigated the effect of the recording electrode position on the spectral content of the signal by using a mathematical model of the women's abdomen. We have then compared the simulated results to actual recordings. On signals with noise reduced with a dedicated algorithm, we have characterized the main frequency components of the signal spectrum in order to compute parameters indicative of different situations: preterm contractions resulting nonetheless in term delivery (i.e. normal contractions) and preterm contractions leading to preterm delivery (i.e. high-risk contractions). A diagnosis system permitted us to discriminate between these different categories of contractions. As the position of the placenta seems to affect the frequency content of electrical activity, we have also investigated in monkeys, with internal electrodes attached on the uterus, the effect of the placenta on the spectral content of the electrical signals.

Results

In women, the best electrode position was the median vertical axis of the abdomen. The discrimination between high risk and normal contractions showed that it was possible to detect a risk of preterm labour as early as at the 27th week of pregnancy (Misclassification Rate range: 11–19.5%). Placental influence on electrical signals was evidenced in animal recordings, with higher energy content in high frequency bands, for signals recorded away from the placenta when compared to signals recorded above the placental insertion. However, we noticed, from pregnancy to labour, a similar evolution of the frequency content of the signal towards high frequencies, whatever the relative position of electrodes and placenta.

Conclusion

On human recordings, this study has proved that it is possible to detect, by non-invasive abdominal recordings, a risk of preterm birth as early as the 27th week of pregnancy. On animal signals, we have evidenced that the placenta exerts a local influence on the characteristics of the electrical activity of the uterus. However, these differences have a small influence on premature delivery risk diagnosis when using proper diagnosis tools.

Background

Studies on the human myometrium have reported on different microarrays containing different sets of genes or ESTs. However each study profiled only a small number of patients due to various constraints. More profiling information would be an addition to our knowledge base of parturition.

Methods

We compiled from five human studies, transcriptional differences between the non pregnant myometrium (NP), preterm myometrium (PTNIL), term myometrium not in labor (TNIL) and term myometrium in labor (TIL). Software modules developed by the Draghici's group at Wayne State University (Detroit, MI, USA) were used to propose a hierarchical list of several KEGG pathways most likely adjusted to changes observed in microarray experiments.

Results

The differential expression of 118 genes could be dispatched in 14 main KEGG pathways that were the most representative of the changes seen in NP and PTNIL, versus TNIL or TIL. Despite the potential of multiple pitfalls inherent to the use of the microarray technology, gene module analysis of the myometrial transcriptome reveals the activation of precise signaling pathways, some of which may have been under evaluated.

Conclusion

The remodelling and maturation processes that the uterus undergoes in pregnancy appear clearly as phenomena which last during the full course of gestation. It is attested by the nature of the main signaling pathways represented, in the comparison of the PTNIL versus TNIL uterus. Comparatively, the onset of labor is a phenomenon which remains less well characterized by these methods of analysis, possibly because it is a phenomenon occurring in too short a window to have been grasped by the studies carried out up to now.