Perinatal growth hormone (GH) physiology : effect of GH-releasing factor on maternal and fetal secretion of pituitary and placental GH.

To study regulation of the secretion of human pituitary GH (hGH) and placental GH (hPGH) in the pregnant woman and human fetus, the GH-releasing factor Sermorelin [GRF-(l–29)-NH2] was administered to pregnant women at term (n = 5), just before elective cesarean section; saline was administered in control studies (n = 5). The effects of GRF-(1–29)-NH2 administration on maternal and fetal serum concentrations of hGH and GRF-(l–29)-NH2 and maternal serum levels of hPGH were evaluated at birth. The mean time span between injection and birth was 20 min (range, 15–25 min). Cord serum hGH concentrations were similar in infants of GRF-(1–29)-NH2-injected mothers and control infants. GRF-(l–29)-NH2 elicited a consistent but small rise in maternal hGH serum concentrations (P = 0.08), whereas hPGH concentrations remained unaltered. Finally, GRF-(l–29)-NH2 concentrations were undetectable in cord serum, but readily detectable in concomitantly obtained maternal serum. In conclusion, these data suggest that hGH secretion in the pregnant woman at term is suppressed at the pituitary level, that GRF does not affect hPGH secretion, and that fetal hGH secretion is independent of circulating maternal GRF, probably because of lack of transplacental GRF passage

An automatic system for in vitro cell migration studies

This paper describes a system for in vitro cell migration analysis. Adult neural stem/progenitor cells are studied using time-lapse bright-field microscopy and thereafter stained immunohistochemically to find and distinguish undifferentiated glial progenitor cells and cells having differentiated into type-1 or type-2 astrocytes. The cells are automatically segmented and tracked through the time-lapse sequence. An extension to the Chan-Vese Level Set segmentation algorithm, including two new terms for specialized growing and pruning, made it possible to resolve clustered cells, and reduced the tracking error by 65%. We used a custom-built manual correction module to form a ground truth used as a reference for tracked cells that could be identified from the fluorescence staining. On average, the tracks were correct 95% of the time, using our new segmentation. The tracking, or association of segmented cells, was performed using a 2-state Hidden Markov Model describing the random behaviour of the cells. By re-estimating the motion model to conform with the segmented data we managed to reduce the number of tracking parameters to essentially only one. Upon characterization of the cell migration by the HMM state occupation function, it was found that glial progenitor cells were moving randomly 2/3 of the time, while the type-2 astrocytes showed a directed movement 2/3 of the time. This finding indicates possibilities for cell-type specific identification and cell sorting of live cells based on specific movement patterns in individual cell populations, which would have valuable applications in neurobiological research