Table 2.

Summary of statistical analyses of internalization data

Graph	Function	Regression equation	Coefficient of determination (R2)	Probability of random relationship	Sample size	ANCOVA comparison of slopes probability
4 C	Fc vs. FcRn	y = 0.210x + 54.4	0.738	p = 7.9 × 10−11	35	p = 4.5 × 10−8
	Dextran vs. FcRn	y = 0.0116x + 70.7	0.142	p = 0.0283	35
4 D	Fc/dextran vs. FcRn	y = 0.002x + 0.962	0.601	p = 7.3 × 10−8	35
4 E	T250Q/M428L vs. FcRn	y = 0.316x + 67.0	0.707	p = 8.6 × 10−5	15	p = 0.000056
	H435A vs. FcRn	y = −.0022x + 81.2	0.005	p = 0.9333	17
5 I	Fc vs. FcRn	y = 0.00152x + 55.5	0.443	p = 0.0005	23	p = 0.000078
	Fc vs. FcRn − competition	y = 0.0035x + 53.7	0.087	p = 0.206	20
5 J	T250Q/M428L vs. FcRn	y = 0.202x + 63.9	0.608	p = 1.15 × 10−5	23	p = 0.000042
	T250Q/M428L vs. FcRn competition	y = 0.025x + 65.1	0.311	p = 0.00860	21
5 K	Fc vs. FcRn	y = 0.133x + 44.9	0.740	p = 5.67 × 10−5	21	p = 0.300
	Fc vs. FcRn H435A competition	y = 0.117x + 36.6	0.870	p = 5.16 × 10−13	28
5 L	T250Q/M428L vs. FcRn	y = 0.115x + 83.6	0.280	p = 0.0079	24	p = 0.076
	T250Q/M428L vs. FcRn, H435A competition	y = 0.195x + 48.3	0.775	p = 6.69 × 10−9	25
7 E	Fc vs. FcRn	y = 0.196x + 52.8	0.894	p = 3.51 × 10−13	26	p = 6.70 × 10−15
	Dextran vs. FcRn	y = 0.023x + 71.1	0.312	p = 0.003	26
7 F	Fc vs. FcRn	y = 0.238x + 33.6	0.762	p = 7.0 × 10−7	21	p = 1.25 × 10−7
	Dextran vs. FcRn	y = 0.014x + 78.0	0.040	p = 0.384	21
8 E	Fc vs. FcRn	y = 0.078x + 65.6	0.506	p = 1.4 × 10−4	23