Acceptor binding energies in GaN and AlN

We employ effective mass theory for degenerate hole-bands to calculate the acceptor binding energies for Be, Mg, Zn, Ca, C and Si substitutional acceptors in GaN and AlN. The calculations are performed through the 6$\times$6 Rashba-Sheka-Pikus and the Luttinger-Kohn matrix Hamiltonians for wurtzite (WZ) and zincblende (ZB) crystal phases, respectively. An analytic representation for the acceptor pseudopotential is used to introduce the specific nature of the impurity atoms. The energy shift due to polaron effects is also considered in this approach. The ionization energy estimates are in very good agreement with those reported experimentally in WZ-GaN. The binding energies for ZB-GaN acceptors are all predicted to be shallower than the corresponding impurities in the WZ phase. The binding energy dependence upon the crystal field splitting in WZ-GaN is analyzed. Ionization levels in AlN are found to have similar `shallow' values to those in GaN, but with some important differences, which depend on the band structure parameterizations, especially the value of crystal field splitting used.Comment: REVTEX file - 1 figur

The prognostic impact of anti-cancer immune response: a novel classification of cancer patients

Until now, the anatomic extent of tumor (TNM classification) has been, by far, the most important factor to predict the prognosis of colorectal cancer patients. However, in recent years, data collected from large cohorts of human cancers demonstrated that the immune contexture of the primary tumors is an essential prognostic factor for patients' disease-free and overall survival. Global analysis of tumor microenvironment showed that the nature, the functional orientation, the density, and the location of adaptive immune cells within distinct tumor regions influence the risk of relapse events. An immune classification of the patients was proposed based on the density and the immune cell location within the tumor. The immune classification has a prognostic value that is superior to the TNM classification, and tumor invasion is statistically dependent on the host immune reaction. Tumor and immunological markers predicted by systems biology methods are involved in the shaping of an efficient immune reaction and can serve as targets for novel therapeutic approaches. Thus, the strength of the immune reaction could advance our understanding of cancer evolution and have important consequences in clinical practice

Tumor immunosurveillance in human cancers

Until now, the anatomic extent of tumor (TNM classification) has been by far the most important factor to predict the prognosis of colorectal cancer patients. However, in recent years, data collected from large cohorts of human cancers demonstrated that the immune contexture of the primary tumors is an essential prognostic factor for patients’ disease-free and overall survival. Tumoral and immunological markers predicted by systems biology methods are involved in the shaping of an efficient immune reaction and can serve as targets for novel therapeutic approaches. Global analysis of tumor microenvironment showed that the nature, the functional orientation, the density, and the location of adaptive immune cells within distinct tumor regions influence the risk of relapse events. The density and the immune cell location within the tumor have a prognostic value that is superior to the TNM classification, and tumor invasion is statistically dependent on the host-immune reaction. Thus, the strength of the immune reaction could advance our understanding of cancer evolution and have important consequences in clinical practice