Placental determinants of fetal growth: identification of key factors in the insulin-like growth factor and cytokine systems using artificial neural networks

Table 2 List of variables analysed using Artificial Neural Networks (ANNS) and their linear correlation index (r²) with each target variable.

	Variables	Correlation index (r²)
1	Chronological age of the mother at delivery (years)	0,11
2	Sex of the newborn	0
3	Gestational age (weeks)	0,22
4	Other siblings (yes or No)	0,001
5	Number of other siblings	0,005
6	Number of previous abortions	0,000
7	Total placental protein content in lysates (mg/ml)	0,007
8	IGF-II concentration in placental lysates (ng/mg)	0,16
9	IGFBP-2 concentration in placental lysates (ng/mg)	0,05
10	IL-6 concentration in placental lysates (pg/mg)	0,09
11	TNF-α concentration in placental lysates (ng/mg)	0,05
12	IGF-I relative gene expression in placenta (A.U./18S, UBQ)	0,01
13	IGF-II relative gene expression in placenta (A.U./18S, UBQ)	0,02
14	IGFBP-1 relative gene expression in placenta (A.U./18S, UBQ)	0,05
15	IGFBP-2 relative gene expression in placenta (A.U./18S, UBQ)	0,08
16	IL-6 relative gene expression in placenta (A.U./18S, UBQ)	0,16

Biochemical data were measured as specified in materials and methods. Gene expressions are in arbitrary units (AU) with respect to two house-keeping genes, 18 S ribosomal RNA (18S) and ubiquitin (UBQ). Specific protein concentrations in placental lysates are ng or pg per mg of placenta.

ISSN: 1471-2431