Two least squares methods of estimating nutrient requirements from growth data were compared. One method involved fitting a broken line by the method of least squares. The requirement was taken as the abscissa of the breakpoint in the curve. The other method involved fitting an appropriate exponential function to the growth data and estimating the requirement as the abscissa of the point on the fitted curve whose ordinate was 95% of the upper asymptote. For the nine sets of data studied, the broken line provided adequate fits for only six. The nonlinear models provided adequate fits for all the data studied. When both the broken line and the chosen nonlinear model provided adequate fits, the estimated requirements were nearly the same. However, the consistently good fits obtained with the nonlinear models suggest that this approach may generally be more useful.

No abstract

Laying hens were killed at hourly intervals during the 26-h laying cycle. The 3 largest follicles of the size hierarchy were removed and plasma samples were obtained from the same hens. The follicle walls and the plasma were assayed by RIA for estrogen (E), progesterone (P4), and testosterone (T). The data show that for E and T there is an inverse relationship between follicle size and hormone concentration. There is no such difference for P4. Both E and T show a significant drop immediately after ovulation; P4 does not. Both T and E concentrations rise significantly and synchronously at about 4 and at 8 h after ovulation. The OAAD assay of plasma shows a peak of LH about that time. P4 does not show such a rise in concentration. About 8 to 10 h prior to the next ovulation T concentration in all 3 follicles begins to rise, P4 rises only in the largest follicle and E only in the smallest. All three steroids reach highly significant peaks about 4 to 6 h prior to the next ovulation. Both OAAD and RIA detect plasma LH peaks at about that time. Plasma E and follicle E peak synchronously at 4 to 8 h; T peaks occur at 10 to 12 h after ovulation and are asynchronous with the T follicle peaks. All 3 steroids begin to rise in the plasma about 10 h prior to the next ovulation and all 3 peak together about 4 to 5 h prior to ovulation. The present data do not allow to distinguish between rates of steroid synthesis and their release into the plasma. Whether the steroid peaks occurring in both follicles and plasma shortly before the next ovulation are caused by LH or are the cause of its release remains to be determined.

Daily rhythmicity of serum testosterone concentration in the mature male laboratory rat was examined under various lighting schedules. In rats living in a standard light cycle (12-h light, 12-h dark; lights on at 0600 h), a trimodal rhythm was predominant, with elevations near 0200, 1200, and 1800 h. This pattern was reasonably stable in seven different studies, despite differences in experimental design, method of blood collection, anesthesia, and whether individual rats were sampled once or repeatedly, and was found both in groups of animals and in individuals, including a study using 40-day-old rats. In constant illumination, the pattern was disrupted, but in constant darkness the trimodal pattern was maintained, indicating that the rhythm is endogenous. In a reversed light cycle (12-h dark, 12-h light; lights on at 1800 h), the "midday" elevation was reversed; in an altered light cycle (12-h dark, 12-h light; lights on at 2300 h), the time of the "midday" elevation was shifted. Serum testosterone concentration was higher during the light phase than the dark phase, and was higher in constant light than in constant darkness. A seasonal shift in the daily rhythmicity of serum testosterone concentration is suggested. The trimodal rhythmicity contrasts with the circadian rhythmicity of other hormones. Its functional role in the life of the animal is unknown.