Extension of Information Geometry to Non-statistical Systems: Some Examples

Our goal is to extend information geometry to situations where statistical modeling is not obvious. The setting is that of modeling experimental data. Quite often the data are not of a statistical nature. Sometimes also the model is not a statistical manifold. An example of the former is the description of the Bose gas in the grand canonical ensemble. An example of the latter is the modeling of quantum systems with density matrices. Conditional expectations in the quantum context are reviewed. The border problem is discussed: through conditioning the model point shifts to the border of the differentiable manifold.Comment: 8 pages, to be published in the proceedings of GSI2015, Lecture Notes in Computer Science, Springe

Transverse Radial Flow Effects on Two- and Three-Particle Angular Correlations

We use a simple a transverse radial boost scenario coupled to PYTHIA events to illustrate the impact radial flow may have on two- and three-particle correlation functions measured in heavy-ion collisions. We show that modest radial velocities can impart strong modifications to the correlation functions, some of which may be interpreted as same side ridge and away side structure that can mimic conical emission.Comment: 7 figures, 9 pages, Material presented in part by Pruneau at HOC 07, Montreal, Canada Accepted for publication in Nucl Phys A (Jan 2008

Lorentz invariance relations between parton distributions and the Wandzura-Wilczek approximation

The violation of the so-called Lorentz invariance relations between parton distribution functions is considered in a model independent way. It is shown that these relations are not violated in a generalized Wandzura-Wilczek approximation, indicating that numerically their violation may be small.Comment: 13 pages, added references, minor changes, to appear in Phys. Lett.

Double spin asymmetry A_{LT} in direct photon production

We study the longitudinal-transverse double spin asymmetry $A_{LT}$ for direct photon production in nucleon-nucleon scattering by using the collinear twist-3 approach. This asymmetry, which, for instance, could be measured at RHIC, contains a complete set of collinear twist-3 correlation functions in a transversely polarized nucleon.Comment: 9 pages, 1 figur

Transverse spin asymmetries for W-production in proton-proton collisions

We study parity-even and parity-odd polarization observables for the process $p \, p \to l^{\pm} \, X$, where the lepton comes from the decay of a $W$-boson. By using the collinear twist-3 factorization approach, we consider the case when one proton is transversely polarized, while the other is either unpolarized or longitudinally polarized. These observables give access to two particular quark-gluon-quark correlation functions, which have a direct relation to transverse momentum dependent parton distributions. We present numerical estimates for RHIC kinematics. Measuring, for instance, the parity-even transverse single spin correlation would provide a crucial test of our current understanding of single spin asymmetries in the framework of QCD.Comment: 10 page

Human papillomavirus and post-transplant cutaneous squamous-cell carcinoma:a multicenter, prospective cohort study

Organ transplant recipients (OTRs) have a 100-fold increased risk of cutaneous squamous cell carcinoma (cSCC). We prospectively evaluated the association between β genus human papillomaviruses (βPV) and keratinocyte carcinoma in OTRs. Two OTR cohorts without cSCC were assembled: cohort 1 was transplanted in 2003-2006 (n =\ua0274) and cohort 2 was transplanted in 1986-2002 (n =\ua0352). Participants were followed until death or cessation of follow-up in 2016. βPV infection was assessed in eyebrow hair by using polymerase chain reaction-based methods. βPV IgG seroresponses were determined with multiplex serology. A competing risk model with delayed entry was used to estimate cumulative incidence of histologically proven cSCC and the effect of βPV by using a multivariable Cox regression model. Results are reported as adjusted hazard ratios (HRs). OTRs with 5 or more different βPV types in eyebrow hair had 1.7 times the risk of cSCC vs OTRs with 0 to 4 different types (HR 1.7, 95% confidence interval 1.1-2.6). A similar risk was seen with high βPV loads (HR 1.8, 95% confidence interval 1.2-2.8). No significant associations were seen between serum antibodies and cSCC or between βPV and basal cell carcinoma. The diversity and load of βPV types in eyebrow hair are associated with cSCC risk in OTRs, providing evidence that βPV is associated with cSCC carcinogenesis and may present a target for future preventive strategies

Beta-HPV 5 and 8 E6 Promote p300 Degradation by Blocking AKT/p300 Association

The E6 oncoprotein from high-risk genus alpha human papillomaviruses (α-HPVs), such as HPV 16, has been well characterized with respect to the host-cell proteins it interacts with and corresponding signaling pathways that are disrupted due to these interactions. Less is known regarding the interacting partners of E6 from the genus beta papillomaviruses (β-HPVs); however, it is generally thought that β-HPV E6 proteins do not interact with many of the proteins known to bind to α-HPV E6. Here we identify p300 as a protein that interacts directly with E6 from both α- and β-HPV types. Importantly, this association appears much stronger with β-HPV types 5 and 8-E6 than with α-HPV type 16-E6 or β-HPV type 38-E6. We demonstrate that the enhanced association between 5/8-E6 and p300 leads to p300 degradation in a proteasomal-dependent but E6AP-independent manner. Rather, 5/8-E6 inhibit the association of AKT with p300, an event necessary to ensure p300 stability within the cell. Finally, we demonstrate that the decreased p300 protein levels concomitantly affect downstream signaling events, such as the expression of differentiation markers K1, K10 and Involucrin. Together, these results demonstrate a unique way in which β-HPV E6 proteins are able to affect host-cell signaling in a manner distinct from that of the α-HPVs

Integrated Analysis of Residue Coevolution and Protein Structure in ABC Transporters

Intraprotein side chain contacts can couple the evolutionary process of amino acid substitution at one position to that at another. This coupling, known as residue coevolution, may vary in strength. Conserved contacts thus not only define 3-dimensional protein structure, but also indicate which residue-residue interactions are crucial to a protein’s function. Therefore, prediction of strongly coevolving residue-pairs helps clarify molecular mechanisms underlying function. Previously, various coevolution detectors have been employed separately to predict these pairs purely from multiple sequence alignments, while disregarding available structural information. This study introduces an integrative framework that improves the accuracy of such predictions, relative to previous approaches, by combining multiple coevolution detectors and incorporating structural contact information. This framework is applied to the ABC-B and ABC-C transporter families, which include the drug exporter P-glycoprotein involved in multidrug resistance of cancer cells, as well as the CFTR chloride channel linked to cystic fibrosis disease. The predicted coevolving pairs are further analyzed based on conformational changes inferred from outward- and inward-facing transporter structures. The analysis suggests that some pairs coevolved to directly regulate conformational changes of the alternating-access transport mechanism, while others to stabilize rigid-body-like components of the protein structure. Moreover, some identified pairs correspond to residues previously implicated in cystic fibrosis

Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes