The paper presents the stratigraphy of Paleogene strata from the central part of carbonate Dinarides. The carbonate and the clastic rock units were stu died. Their contact with underlying Senonian limes tone is marked by unconformity as a result of Laramian tectonic phase. The unconformity is denoted by the abundance of bauxite deposits. The abundance of calcareous nanoplancton species as well as ben tic foraminifera points at the sedimentation of Paleogene strata during the Eocene period. The succession of sediments with easily recognizeable transgressive, inundation and regres sive features has been established. Lithostratigraphical characteristics enabled the distinguishing of larger lithofacies groups. The simultaneousness of carbonate rocks with lower part of clastic succession as well as the transitionallitho· facies have been approved. The simultaneous overburden of bauxite deposits regardless of its lithology (carbonate of clastic) speaks in favour of the unite bauxitebearing phase.

In this paper we investigate gradings on tame blocks of group algebras whose defect group is dihedral. We classify gradings on an arbitrary dihedral block up to graded Morita equivalence. We do this by computing the group of outer automorphisms that fix the isomorphism classes of simple modules. We also show how to grade these blocks via transfer of gradings via dervied equivalences.

We study the chemisorption of CO molecule into sites of different coordination on (111) surfaces of late $4d$ and $5d$ transition metals. In an attempt to solve the well-known CO adsorption puzzle, i.e., discrepancies of adsorption site preferences with experiment which appear in the standard density functional theory calculations, we have applied the relatively new van der Waals-density functional of nonlocal correlation. In all considered cases this reduces or completely solves the site preference discrepancies and improves the value of the adsorption energy. By introducing a cutoff distance for nonlocal interaction we can pinpoint the length scale at which the correlation plays a major role in the systems considered.

The use of biomarkers ensures breast cancer patients receive optimal treatment. Established biomarkers such as estrogen receptor (ER) and progesterone receptor (PR) have been playing significant roles in the selection and management of patients for endocrine therapy. HER2 is a strong predictor of response to trastuzumab. Recently, the roles of ER as a negative and HER2 as a positive indicator for chemotherapy have been established. Ki67 has traditionally been recognized as a poor prognostic factor, but recent studies suggest that measurement of Ki67-positive cells during treatment will more effectively predict treatment efficacy for both anti-hormonal and chemotherapy. p53 mutations are found in 20–35% of human breast cancers and are associated with aggressive disease with poor clinical outcome when the DNA-binding domain is mutated. The utility of cyclin D1 as a predictor of breast cancer prognosis is controversial, but cyclin D1b overexpression is associated with poor prognosis. Likewise, overexpression of the low molecular weight form of cyclin E1 protein predicts poor prognosis. Breast cancers from BRCA1/2 carriers often show high nuclear grades, negativity to ER/PR/HER2, and p53 mutations, and thus, are associated with poor prognosis. The prognostic values of other molecular markers, such as p14ARF, TBX2/3, VEGF in breast cancer are also discussed. Careful evaluation of these biomarkers with current treatment modality is required to determine whether their measurement or monitoring offer significant clinical benefits.