Development and Validation of an Epitope Prediction Tool for Swine (PigMatrix) Based on the Pocket Profile Method

Background: T cell epitope prediction tools and associated vaccine design algorithms have accelerated the development of vaccines for humans. Predictive tools for swine and other food animals are not as well developed, primarily because the data required to develop the tools are lacking. Here, we overcome a lack of T cell epitope data to construct swine epitope predictors by systematically leveraging available human information. Applying the “pocket profile method”, we use sequence and structural similarities in the binding pockets of human and swine major histocompatibility complex proteins to infer Swine Leukocyte Antigen (SLA) peptide binding preferences. We developed epitope-prediction matrices (PigMatrices), for three SLA class I alleles (SLA-1*0401, 2*0401 and 3*0401) and one class II allele (SLA-DRB1*0201), based on the binding preferences of the best-matched Human Leukocyte Antigen (HLA) pocket for each SLA pocket. The contact residues involved in the binding pockets were defined for class I based on crystal structures of either SLA (SLA-specific contacts, Ssc) or HLA supertype alleles (HLA contacts, Hc); for class II, only Hc was possible. Different substitution matrices were evaluated (PAM and BLOSUM) for scoring pocket similarity and identifying the best human match. The accuracy of the PigMatrices was compared to available online swine epitope prediction tools such as PickPocket and NetMHCpan. Results: PigMatrices that used Ssc to define the pocket sequences and PAM30 to score pocket similarity demonstrated the best predictive performance and were able to accurately separate binders from random peptides. For SLA-1*0401 and 2*0401, PigMatrix achieved area under the receiver operating characteristic curves (AUC) of 0.78 and 0.73, respectively, which were equivalent or better than PickPocket (0.76 and 0.54) and NetMHCpan version 2.4 (0.41 and 0.51) and version 2.8 (0.72 and 0.71). In addition, we developed the first predictive SLA class II matrix, obtaining an AUC of 0.73 for existing SLA-DRB1*0201 epitopes. Notably, PigMatrix achieved this level of predictive power without training on SLA binding data. Conclusions: Overall, the pocket profile method combined with binding preferences from HLA binding data shows significant promise for developing T cell epitope prediction tools for pigs. When combined with existing vaccine design algorithms, PigMatrix will be useful for developing genome-derived vaccines for a range of pig pathogens for which no effective vaccines currently exist (e.g. porcine reproductive and respiratory syndrome, influenza and porcine epidemic diarrhea)

Time for T? Immunoinformatics addresses the challenges of vaccine design for neglected tropical and emerging infectious diseases

Vaccines have been invaluable for global health, saving lives and reducing healthcare costs, while also raising the quality of human life. However, newly emerging infectious diseases (EID) and more well-established tropical disease pathogens present complex challenges to vaccine developers; in particular, neglected tropical diseases, which are most prevalent among the world’s poorest, include many pathogens with large sizes, multistage life cycles and a variety of nonhuman vectors. EID such as MERS-CoV and H7N9 are highly pathogenic for humans. For many of these pathogens, while their genomes are available, immune correlates of protection are currently unknown. These complexities make developing vaccines for EID and neglected tropical diseases all the more difficult. In this review, we describe the implementation of an immunoinformatics-driven approach to systematically search for key determinants of immunity in newly available genome sequence data and design vaccines. This approach holds promise for the development of 21st century vaccines, improving human health everywhere

Coronary artery surgery: cardiotomy suction or cell salvage?

Coronary artery bypass grafting (CABG) today results in what may be regarded as acceptable levels of blood loss with many institutions avoiding allogeneic red cell transfusion in over 60% of their patients. The majority of cardiac surgeons employ cardiotomy suction to preserve autologous blood during on-pump coronary artery bypass surgery; however the use of cardiotomy suction is associated with a more pronounced systemic inflammatory response and a resulting coagulopathy as well as exacerbating the microembolic load. This leads to a tendency to increased blood loss, transfusion requirement and organ dysfunction. Conversely, the avoidance of cardiotomy suction in coronary artery bypass surgery is not associated with an increased transfusion requirement. There is therefore no indication for the routine use of cardiotomy suction in on-pump coronary artery surgery

Observation of Two New Excited Ξb0 States Decaying to Λb0 K-π+

Two narrow resonant states are observed in the Λb0K-π+ mass spectrum using a data sample of proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the LHCb experiment and corresponding to an integrated luminosity of 6 fb-1. The minimal quark content of the Λb0K-π+ system indicates that these are excited Ξb0 baryons. The masses of the Ξb(6327)0 and Ξb(6333)0 states are m[Ξb(6327)0]=6327.28-0.21+0.23±0.12±0.24 and m[Ξb(6333)0]=6332.69-0.18+0.17±0.03±0.22 MeV, respectively, with a mass splitting of Δm=5.41-0.27+0.26±0.12 MeV, where the uncertainties are statistical, systematic, and due to the Λb0 mass measurement. The measured natural widths of these states are consistent with zero, with upper limits of Γ[Ξb(6327)0]<2.20(2.56) and Γ[Ξb(6333)0]<1.60(1.92) MeV at a 90% (95%) credibility level. The significance of the two-peak hypothesis is larger than nine (five) Gaussian standard deviations compared to the no-peak (one-peak) hypothesis. The masses, widths, and resonant structure of the new states are in good agreement with the expectations for a doublet of 1D Ξb0 resonances

Measurement of the electron reconstruction efficiency at LHCb

The single electron track-reconstruction efficiency is calibrated using a sample corresponding to 1.3 fb−1 of pp collision data recorded with the LHCb detector in 2017. This measurement exploits B+→ J/ψ(e+e−)K+ decays, where one of the electrons is fully reconstructed and paired with the kaon, while the other electron is reconstructed using only the information of the vertex detector. Despite this partial reconstruction, kinematic and geometric constraints allow the B meson mass to be reconstructed and the signal to be well separated from backgrounds. This in turn allows the electron reconstruction efficiency to be measured by matching the partial track segment found in the vertex detector to tracks found by LHCb's regular reconstruction algorithms. The agreement between data and simulation is evaluated, and corrections are derived for simulated electrons in bins of kinematics. These correction factors allow LHCb to measure branching fractions involving single electrons with a systematic uncertainty below 1%