Matrix diagonalization and exact solution of the k-photon Jaynes-Cummings model

We study and exactly solve the two-photon and k-photon Jaynes-Cummings models by using a novelty algebraic method. This algebraic method is based on the Pauli matrices realization and the tilting transformation of the $SU(2)$ group and let us diagonalize the Hamiltonian of these models by properly choosing the coherent state parameters of the transformation. Finally, we explicitly obtain the energy spectrum and eigenfunctions for each model.Comment: 12 page

Poster: Documenting Horizons of Interpretation in Philosophy

This poster presentation describes a project currently underway at the Faculty of Filosofía y Letras, Universidad Nacional Autónoma de México (UNAM). It has been funded by a grant from the Programa de Apoyo a Proyectos para la Innovación y Mejoramiento de la Enseñanza (PAPIME), a university endowment program for innovation in education. It is a collaborative documentation project of the individual and collective processes of research and writing of a group of 25 researchers, working on papers about the contemporary strategies of appropriation of the antiquity and aims to use innovative web-based technology to document different data of the research/writing process and to create a visualization model to use the data for educative and didactical purposes

CXCL17 Is a Specific Diagnostic Biomarker for Severe Pandemic Influenza A(H1N1) That Predicts Poor Clinical Outcome.

The C-X-C motif chemokine ligand 17 (CXCL17) is chemotactic for myeloid cells, exhibits bactericidal activity, and exerts anti-viral functions. This chemokine is constitutively expressed in the respiratory tract, suggesting a role in lung defenses. However, little is known about the participation of CXCL17 against relevant respiratory pathogens in humans. Here, we evaluated the serum levels and lung tissue expression pattern of CXCL17 in a cohort of patients with severe pandemic influenza A(H1N1) from Mexico City. Peripheral blood samples obtained on admission and seven days after hospitalization were processed for determinations of serum CXCL17 levels by enzyme-linked immunosorbent assay (ELISA). The expression of CXCL17 was assessed by immunohistochemistry (IHQ) in lung autopsy specimens from patients that succumbed to the disease. Serum CXCL17 levels were also analyzed in two additional comparative cohorts of coronavirus disease 2019 (COVID-19) and pulmonary tuberculosis (TB) patients. Additionally, the expression of CXCL17 was tested in lung autopsy specimens from COVID-19 patients. A total of 122 patients were enrolled in the study, from which 68 had pandemic influenza A(H1N1), 24 had COVID-19, and 30 with PTB. CXCL17 was detected in post-mortem lung specimens from patients that died of pandemic influenza A(H1N1) and COVID-19. Interestingly, serum levels of CXCL17 were increased only in patients with pandemic influenza A(H1N1), but not COVID-19 and PTB. CXCL17 not only differentiated pandemic influenza A(H1N1) from other respiratory infections but showed prognostic value for influenza-associated mortality and renal failure in machine-learning algorithms and regression analyses. Using cell culture assays, we also identified that human alveolar A549 cells and peripheral blood monocyte-derived macrophages increase their CXCL17 production capacity after influenza A(H1N1) pdm09 virus infection. Our results for the first time demonstrate an induction of CXCL17 specifically during pandemic influenza A(H1N1), but not COVID-19 and PTB in humans. These findings could be of great utility to differentiate influenza and COVID-19 and to predict poor prognosis specially at settings of high incidence of pandemic A(H1N1). Future studies on the role of CXCL17 not only in severe pandemic influenza, but also in seasonal influenza, COVID-19, and PTB are required to validate our results

Corrigendum: CXCL17 Is a Specific Diagnostic Biomarker for Severe Pandemic Influenza A(H1N1) That Predicts Poor Clinical Outcome.

[This corrects the article DOI: 10.3389/fimmu.2021.633297.]