Background-Adrenomedullin (AM) is a vasodilating peptide involved in the regulation of circulatory homeostasis and in the pathophysiology of certain cardiovascular diseases. Levels of AM are markedly increased in the fetoplacental circulation during pregnancy, although its function there remains unknown. To clarify the physiological functions of AM, we chose a gene-targeting strategy in mice. Methods and Results-Targeted null mutation of the AM gene is lethal in utero: the mortality rate among AM Ϫ/Ϫ embryos was Ͼ80% at E13.5. The most apparent abnormality in surviving AM Ϫ/Ϫ embryos at E13.5 to E14.0 was severe hemorrhage, readily observable under the skin and in visceral organs. Hemorrhage was not detectable at E12.5 to E13.0, although the yolk sac lacked well-developed vessels. Electron microscopic examination showed endothelial cells to be partially detached from the basement structure at E12.5 in vitelline vessels and hepatic capillaries, which allowed efflux of protoerythrocytes through the disrupted barrier. The basement membrane was not clearly recognizable in the aorta and cervical artery, and the endothelial cells stood out from the wall of the lumen, only partially adhering to the basement structure. AM ϩ/Ϫ mice survived to adulthood but exhibited elevated blood pressures with diminished nitric oxide production. Conclusions-AM is indispensable for the vascular morphogenesis during embryonic development and for postnatal regulation of blood pressure by stimulating nitric oxide production.

Heart rate variability (HRV), extracted from an electrocardiogram, is known to be a noninvasive indicator reflecting the dynamic interplay between perturbations to cardiovascular function and the dynamic response of the cardiovascular regulatory system. Photoplethysmography (PPG) is a noninvasive method to monitor arterial oxygen saturation on a continuous basis. Given the rich cardiovascular information in the PPG signal, and the ubiquity and simplicity of pulse oximetry, we are investigating the feasibility of acquiring dynamics pertaining to the autonomic nervous system from PPG waveforms. To do this, we are quantifying PPG variability (PPGV). Detailed algorithmic approaches for extracting accurate PPGV signals are presented. We compare PPGV to HRV by computing time and frequency domain parameters often associated with HRV measurements, as well as approximate entropy calculations. Our results demonstrate that the parameters of PPGV are highly correlated with the parameters of HRV. Thus, our results indicate that PPGV could be used as an alternative measurement of HRV.