SLESIS-R: an improved score for prediction of serious infection in patients with systemic lupus erythematosus based on the RELESSER prospective cohort.

Objective: To develop an improved score for prediction of severe infection in patients with systemic lupus erythematosus (SLE), namely, the SLE Severe Infection Score-Revised (SLESIS-R) and to validate it in a large multicentre lupus cohort.

Methods: We used data from the prospective phase of RELESSER (RELESSER-PROS), the SLE register of the Spanish Society of Rheumatology. A multivariable logistic model was constructed taking into account the variables already forming the SLESIS score, plus all other potential predictors identified in a literature review.

Interpretation of the LHCb P_{c} States as Hadronic Molecules and Hints of a Narrow P_{c}(4380).

Three hidden-charm pentaquark P_{c} states, P_{c}(4312), P_{c}(4440), and P_{c}(4457) were revealed in the Λ_{b}^{0}→J/ψpK^{-} process measured by LHCb using both run I and run II data. Their nature is under lively discussion, and their quantum numbers have not been determined. We analyze the J/ψp invariant mass distributions under the assumption that the crossed-channel effects provide a smooth background.

Surprises in threshold antikaon-nucleon physics.

Low energy KN interactions are studied within unitary chiral perturbation theory at next-to-leading order with ten coupled channels. We pay special attention to the recent precise determination of the strong shift and width of the kaonic hydrogen 1s state by the DEAR Collaboration that has challenged our theoretical understanding of this sector of strong interactions. We typically find two classes of solutions, both of them reproducing previous data, that either can or cannot accommodate the DEAR measurements.

Minimum distance probability discriminant analysis for mixed variables.

Minimum distance probability (MDP) is a robust discriminant algorithm based on a distance function. In this article, we generalize the use of MDP to the case of mixed (continuous and categorical) variables by means of the individual-score (IS) distance. This distance assumes an underlying parametric model and is based on the score transformation of the data.