Current approach aims to present clinical and pathological staging models of the cancer at the nanoscale to obtain more accurate assessment for the main factors of the prognostic determinants in the classification for cancer staging.
6, 8, and 10 should be identical, and as factors concerned in those models should confirm basis of the main factors assessment of the prognostic determinants in the classification for cancer staging by the TNM system.
The identical evaluation of the histologic grades for the first three detected tumors of relatively earlier stages by the PSM [3H] N, CSMN, and PSM [14C] N (p < 0.0001) boost the confidence to accept the hypotheses of those models and to comply with the basis of the main factors assessment of the prognostic determinants in the classification for cancer staging by the TNM system.
The consistent results of the perfect correlation between H% and their corresponding averages of energy of the tumor nanoparticle (Eng) revealed that accurate histologic diagnosis is essential element in the specific evaluation of the tumor to confirm the basis of the main factors assessment of the prognostic determinants in the classification for cancer staging by the TNM system.
Normalized ΔCt data were used for classification.
This concatenated feature was used for classification.
‡p<0.01 for classification index.
p = 0.008 for classification index.
Also, few studies have been conducted in developing countries [ 11- 14]; thus, it remains difficult to specify determinants for CS in SSA and to propose a CS classification that facilitates international and local comparisons.
Both results indicate that understory structure, and not a coarse classification of habitat type, may be better determinants for explaining the habitat use of native carnivores in this landscape comprised by native habitat and forest plantations.
