Formation of 24Mg* in the Splitting of 28Si Nuclei by 1-GeV Protons

The 28Si(p, p' gamma)24Mg reaction has been studied at the ITEP accelerator by the hadron-gamma coincidence method for a proton energy of 1 GeV. Two reaction products are detected: a 1368.6-keV gamma-ray photon accompanying the transition of the 24Mg* nucleus from the first excited state to the ground state and a proton p' whose momentum is measured in a magnetic spectrometer. The measured distribution in the energy lost by the proton in interaction is attributed to five processes: the direct knockout of a nuclear alpha cluster, the knockout of four nucleons with a total charge number of 2, the formation of the DeltaSi isobaric nucleus, the formation of the Delta isobar in the interaction of the incident proton with a nuclear nucleon, and the production of a pi meson, which is at rest in the nuclear reference frame. The last process likely corresponds to the reaction of the formation of a deeply bound pion state in the 28P nucleus. Such states were previously observed only on heavy nuclei. The cross sections for the listed processes have been estimated.Comment: 14 pages, 3 figures submitted to JETP Letter

Comparison of printed glycan array, suspension array and ELISA in the detection of human anti-glycan antibodies

Anti-glycan antibodies represent a vast and yet insufficiently investigated subpopulation of naturally occurring and adaptive antibodies in humans. Recently, a variety of glycan-based microarrays emerged, allowing high-throughput profiling of a large repertoire of antibodies. As there are no direct approaches for comparison and evaluation of multi-glycan assays we compared three glycan-based immunoassays, namely printed glycan array (PGA), fluorescent microsphere-based suspension array (SA) and ELISA for their efficacy and selectivity in profiling anti-glycan antibodies in a cohort of 48 patients with and without ovarian cancer. The ABO blood group glycan antigens were selected as well recognized ligands for sensitivity and specificity assessments. As another ligand we selected P1, a member of the P blood group system recently identified by PGA as a potential ovarian cancer biomarker. All three glyco-immunoassays reflected the known ABO blood groups with high performance. In contrast, anti-P1 antibody binding profiles displayed much lower concordance. Whilst anti-P1 antibody levels between benign controls and ovarian cancer patients were significantly discriminated using PGA (p = 0.004), we got only similar results using SA (p = 0.03) but not for ELISA. Our findings demonstrate that whilst assays were largely positively correlated, each presents unique characteristic features and should be validated by an independent patient cohort rather than another array technique. The variety between methods presumably reflects the differences in glycan presentation and the antigen/antibody ratio, assay conditions and detection technique. This indicates that the glycan-antibody interaction of interest has to guide the assay selection

Transcriptional Shift Identifies a Set of Genes Driving Breast Cancer Chemoresistance

Background Distant recurrences after antineoplastic treatment remain a serious problem for breast cancer clinical management, which threats patients’ life. Systemic therapy is administered to eradicate cancer cells from the organism, both at the site of the primary tumor and at any other potential location. Despite this intervention, a significant proportion of breast cancer patients relapse even many years after their primary tumor has been successfully treated according to current clinical standards, evidencing the existence of a chemoresistant cell subpopulation originating from the primary tumor.Methods/Findings To identify key molecules and signaling pathways which drive breast cancer chemoresistance we performed gene expression analysis before and after anthracycline and taxane-based chemotherapy and compared the results between different histopathological response groups (good-, mid- and bad-response), established according to the Miller & Payne grading system. Two cohorts of 33 and 73 breast cancer patients receiving neoadjuvant chemotherapy were recruited for whole-genome expression analysis and validation assay, respectively. Identified genes were subjected to a bioinformatic analysis in order to ascertain the molecular function of the proteins they encode and the signaling in which they participate. High throughput technologies identified 65 gene sequences which were over-expressed in all groups (P ≤ 0·05 Bonferroni test). Notably we found that, after chemotherapy, a significant proportion of these genes were over-expressed in the good responders group, making their tumors indistinguishable from those of the bad responders in their expression profile (P ≤ 0.05 Benjamini-Hochgerg`s method).Conclusions These data identify a set of key molecular pathways selectively up-regulated in post-chemotherapy cancer cells, which may become appropriate targets for the development of future directed therapies against breast cancer.Thanks are due to the Consejería de Economia, Innovación y Ciencia (CEIC) from the Junta de Andalucía and Fondo Europeo de Desarrollo Regional (FEDER)/Fondo de Cohesión Europeo (FSE) to financial support through the Programa Operativo FEDER/FSE de Andalucía 2007-2013 and the research project CTS-5350. The authors also acknowledge financial support by the PN de I+D+i 2006-2009/ISCIII/Ministerio de Sanidad, Servicios Sociales e Igualdad (Spain) and Fondo Europeo de Desarrollo Regional (FEDER) from the European Union, through the research project PI06/90388