Three-photon productions within the $$k_t$$-factorization at the LHC

Recently, the ATLAS data of isolated three-photon production showed that the next-to-leading order (NLO) collinear factorization is not enough to describe experimental data. Therefore, one needs to calculate the cross section beyond the NLO, and as showed later, these data can be well described by the NNLO calculation within the collinear factorization framework. However, it is shown that the $$k_t$$ k t -factorization can be quite successful in describing exclusive and high energy collision processes, henceforth we decided to calculate isolated three-photon production within this framework. In this work we use the Martin, Ryskin, and Watt unintegrated parton distribution functions (MRW UPDFs) at LO and NLO levels, in addition to parton branching (PB) UPDFs in order to calculate cross section which we utilize the KATIE parton level event generator. It will be shown that in contrast to collinear factorization, the $$k_t$$ k t -factorization can describe quiet well the three-photon production ATLAS data. Interestingly our results using the NLO-MRW and PB UPDFs can cover the data within their uncertainty bands, similar to the NNLO collinear results.

Mass spectrometry-based sequencing of the anti-FLAG-M2 antibody using multiple proteases and a dual fragmentation scheme

Antibody sequence information is crucial to understanding the structural basis for antigen binding and enables the use of antibodies as therapeutics and research tools. Here we demonstrate a method for direct de novo sequencing of monoclonal IgG from the purified antibody products. The method uses a panel of multiple complementary proteases to generate suitable peptides for de novo sequencing by LC-MS/MS in a bottom-up fashion. Furthermore, we apply a dual fragmentation scheme, using both stepped high-energy collision dissociation (stepped HCD) and electron transfer high-energy collision dissociation (EThcD) on all peptide precursors. The method achieves full sequence coverage of the monoclonal antibody Herceptin, with an accuracy of 98% in the variable regions. We applied the method to sequence the widely used anti-FLAG-M2 mouse monoclonal antibody, which we successfully validated by remodeling a high-resolution crystal structure of the Fab and demonstrating binding to a FLAG-tagged target protein in Western blot analysis. The method thus offers robust and reliable sequences of monoclonal antibodies.

FRACTAL GEOMETRY AND QUARK-GLUON PLASMA PHYSICS

Incorporating fractal geometry in the Regge-Mueller approach to strong interaction dynamics one may formulate a model for the one-dimensional critical sector of the hadronic 5-matrix in a high energy collision. A non conventional component of the correlation functions in rapidity space is obtained, the phenomenological implications of which are related with the intermittency effects in quark-gluon plasma physics.

Glycoproteome Analysis of Human Serum and Brain Tissue

Protein glycosylation represents one of the most common and heterogeneous post-translational modifications (PTMs) in human biology. Herein, an approach for the enrichment of glycopeptides using multi-lectin weak affinity chromatography (M-LWAC), followed by fractionation of the enriched material, and multi-mode fragmentation LC/MS is described. Two fragmentation methods, high-energy collision induced dissociation (HCD) and electron transfer dissociation (EThcD), were independently analyzed. While each fragmentation method provided similar glycopeptide coverage, there was some dependence on the glycoform identity. From these data a total of 7,503 unique glycopeptides belonging to 666 glycoproteins from the combined tissue types, human serum and brain, were identified. Of these, 617 glycopeptides (192 proteins) were found in both tissues; 2,006 glycopeptides (48 proteins) were unique to serum, and 4,880 glycopeptides (426 proteins) were unique to brain tissue. From 379 unique glycoforms, 1,420 unique sites of glycosylation were identified, with an average of four glycans per site. Glycan occurrences were significantly different between tissue types: serum showed greater glycan diversity whereas brain tissue showed a greater abundance of the high mannose family. Glycosylation co-occurrence rates were determined, which enabled us to infer differences in underlying biosynthetic pathways.