Waddington redux: models and explanation in stem cell and systems biology

Stem cell biology and systems biology are two prominent new approaches to studying cell development. In stem cell biology, the predominant method is experimental manipulation of concrete cells and tissues. Systems biology, in contrast, emphasizes mathematical modeling of cellular systems. For scientists and philosophers interested in development, an important question arises: how should the two approaches relate? This essay proposes an answer, using the model of Waddington’s landscape to triangulate between stem cell and systems approaches. This simple abstract model represents development as an undulating surface of hills and valleys. Originally constructed by C. H. Waddington to visually explicate an integrated theory of genetics, development and evolution, the landscape model can play an updated unificatory role. I examine this model’s structure, representational assumptions, and uses in all three contexts, and argue that explanations of cell development require both mathematical models and concrete experiments. On this view, the two approaches are interdependent, with mathematical models playing a crucial but circumscribed role in explanations of cell development.     

Sequence homology in the metalloproteins; purple acid phosphatase from beef spleen and uteroferrin from porcine uterus

The primary structures of purple acid phosphatase and uteroferrin, two iron-binding glycoproteins isolated from beef spleen and porcine uterine fluids, respectively, have been examined by a combination of tandem mass spectrometry and classical Edman sequencing methods. Reported here are amino acid sequence data covering more than 90% of the primary structures for these two proteins. The sequence data reveal an unexpectedly high degree of homology, greater than 90%, for these two proteins.     

Ultradian rhythmic models of blood pressure variation in normal human daily life

To examine levels and variance structure of systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR), we measured those 3 variables every 7.5 min for 24 h (approximately 192 samples each subject) by ambulatory monitoring in 2 nominated groups of normal volunteers: younger (Y; 8 men, 5 women, 24-44 years) and older (O; 13 men, 12 women, 50-95 years). Y and O did not differ in either sleep or wake means for HR and DBP. Mean SBP in O was 17 mm Hg higher than in Y during wakefulness. Thirty-four subjects had significant low frequency variations (presumably the circadian rhythm) in SBP, DBP and HR, regardless of age. A periodic model fitting the time series required a 9 h feature (rhythm) for Y and O in DBP for best reduction of mean square error. In addition, O regularly showed 3 h features in both SBP and DBP, a 6 h feature in DBP and a 9 h feature in SBP, which were absent in Y. Our results suggest that low-power ultradian rhythms may appear in both SBP and DBP after age 50, and possibly serve as dynamic markers of normal cardiovascular aging.