Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Detection of Successful and Unsuccessful Pregnancies in Mice within Hours of Pairing through Frequency Analysis of High Temporal Resolution Core Body Temperature Data

Fig 5

Wavelet analysis reveals differences within 12 h after the day of pairing indicative of successful pregnancies.

Median wavelet transformations of CBT from all mice, including outliers, for the 3 d before pairing (B, F) and 3 d after pairing (C, G), with time along the X axis (light:dark bars indicate light cycle), period along the Y axis, and increases in power per time per period noted by shift in color from blue to red to white (color map in A). Dotted box (C, G) highlights 12 h region of increased ultradian power in mice that show a post-pairing rise in basal CBT and later come to term (top row, B, C, D, whereas the bottom row [F, G, H] displays those individuals that show an initial elevation in CBT after pairing, but which did not deliver a litter). Each individual’s profile of this boxed region is shown as a 2D maximum-intensity projection (D, H) to illustrate the individual variance, with the 4 outliers, noted previously, highlighted with an “O” on the X axis. Median +/- standard error of the spectral power profiles of these projections (E, I) reveals a significant, broad increase in power with a peak around 3 h periodicity for the mice that came to term (orange) as compared to those that did not (blue). This effect is significant whether outliers are excluded (E, χ2 = 363.2, p = 5.64x10-81) or included (I, χ2 = 128.15, p = 1.04x10-29). Individuals’ max power in the region of the ~3h peak (J) indicates that a majority of mice can be successfully separated by even this highly simplified metric (p = 0.026; dotted line indicates threshold above which a majority of successful pregnancies appear, and no unsuccessful, non-outlier pregnancies appear). Note that outliers from each group appear in the range of the opposite group, highlighting the importance of identifying heterogeneity to improve accuracy.

Fig 5

doi: https://doi.org/10.1371/journal.pone.0160127.g005