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1.
Ecol Lett ; 11(3): 235-44, 2008 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-18070098

RESUMO

Observed patterns of species richness at landscape scale (gamma diversity) cannot always be attributed to a specific set of explanatory variables, but rather different alternative explanatory statistical models of similar quality may exist. Therefore predictions of the effects of environmental change (such as in climate or land cover) on biodiversity may differ considerably, depending on the chosen set of explanatory variables. Here we use multimodel prediction to evaluate effects of climate, land-use intensity and landscape structure on species richness in each of seven groups of organisms (plants, birds, spiders, wild bees, ground beetles, true bugs and hoverflies) in temperate Europe. We contrast this approach with traditional best-model predictions, which we show, using cross-validation, to have inferior prediction accuracy. Multimodel inference changed the importance of some environmental variables in comparison with the best model, and accordingly gave deviating predictions for environmental change effects. Overall, prediction uncertainty for the multimodel approach was only slightly higher than that of the best model, and absolute changes in predicted species richness were also comparable. Richness predictions varied generally more for the impact of climate change than for land-use change at the coarse scale of our study. Overall, our study indicates that the uncertainty introduced to environmental change predictions through uncertainty in model selection both qualitatively and quantitatively affects species richness projections.


Assuntos
Biodiversidade , Meio Ambiente , Modelos Biológicos , Animais , Artrópodes , Aves , Clima , Europa (Continente) , Geografia , Plantas
2.
Int J Oncol ; 8(6): 1127-35, 1996 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-21544473

RESUMO

We report a novel anti-CEA monoclonal antibody (MAb) designated R4, which mediates antibody-dependent cell-mediated cytotoxicity (ADCC) of human colon carcinoma cells and displays differential reactivity for human carcinomas versus the normal counterparts. R4 (IgG1) reacted with the cell surface of 6 colon carcinoma cell lines expressing CEA. Western blot analysis and epitope mapping using native and baculovirus recombinant CEA and non specific cross-reacting antigen (NCA) demonstrated that MAb R4 recognizes a proteinic epitope located on the 3' end of the domain I shared by CEA and NCA molecules. Immunohistochemical analysis demonstrated an intense staining of MAb R4 with the majority of the neoplastic tissues tested, including colon (13/13), stomach (2/2), breast (9/10), lung (7/10) and endometrial (2/4) carcinomas, whereas no reactivity with the correspondent normal tissues was observed. Using human PBLs from healthy donors as effector cells, we have shown that MAb R4 mediated antibody dependent-cell mediated cytotoxicity (ADCC) of human carcinoma cells LS-174T, CBS and WiDr. This activity was enhanced after PBLs activation with interleukin-2 (IL-2). The specificity of MAb R4 for an epitope shared by two tumor overexpressed antigens, CEA and NCA, resulting in an intense reactivity with neoplastic cells and the peculiar property to mediate ADCC, indicate that MAb R4 might be a novel powerful reagent for diagnostic and immunotherapy of carcinoma patients.

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