Future research directions in pneumonia

Pneumonia is a complex pulmonary disease in need of new clinical approaches. Although triggered by a pathogen, pneumonia often results from dysregulations of host defense that likely precede infection. The coordinated activities of immune resistance and tissue resilience then dictate whether and how pneumonia progresses or resolves. Inadequate or inappropriate host responses lead to more severe outcomes such as acute respiratory distress syndrome and to organ dysfunction beyond the lungs and over extended time frames after pathogen clearance, some of which increase the risk for subsequent pneumonia. Improved understanding of such host responses will guide the development of novel approaches for preventing and curing pneumonia and for mitigating the subsequent pulmonary and extrapulmonary complications of pneumonia. The NHLBI assembled a working group of extramural investigators to prioritize avenues of host-directed pneumonia research that should yield novel approaches for interrupting the cycle of unhealthy decline caused by pneumonia. This report summarizes the working group’s specific recommendations in the areas of pneumonia susceptibility, host response, and consequences. Overarching goals include the development of more host-focused clinical approaches for preventing and treating pneumonia, the generation of predictive tools (for pneumonia occurrence, severity, and outcome), and the elucidation of mechanisms mediating immune resistance and tissue resilience in the lung. Specific areas of research are highlighted as especially promising for making advances against pneumonia

Innate immunity of the lung: From basic mechanisms to translational medicine.

The respiratory tract is faced daily with 10,000 L of inhaled air. While the majority of air contains harmless environmental components, the pulmonary immune system also has to cope with harmful microbial or sterile threats and react rapidly to protect the host at this intimate barrier zone. The airways are endowed with a broad armamentarium of cellular and humoral host defense mechanisms, most of which belong to the innate arm of the immune system. The complex interplay between resident and infiltrating immune cells and secreted innate immune proteins shapes the outcome of host-pathogen, host-allergen, and host-particle interactions within the mucosal airway compartment. Here, we summarize and discuss recent findings on pulmonary innate immunity and highlight key pathways relevant for biomarker and therapeutic targeting strategies for acute and chronic diseases of the respiratory tract. (c) 2018 S. Karger AG, Base

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion

Measurement of single-diffractive dijet production in proton–proton collisions at √s=8Te with the CMS and TOTEM experiments

Measurements are presented of the single-diffractive dijet cross section and the diffractive cross section as a function of the proton fractional momentum loss ξ and the four-momentum transfer squared t. Both processes pp→pX and pp→Xp, i.e. with the proton scattering to either side of the interaction point, are measured, where X includes at least two jets; the results of the two processes are averaged. The analyses are based on data collected simultaneously with the CMS and TOTEM detectors at the LHC in proton–proton collisions at s=8Te during a dedicated run with β∗=90m at low instantaneous luminosity and correspond to an integrated luminosity of 37.5nb-1. The single-diffractive dijet cross section σjjpX, in the kinematic region ξ< 0.1 , 0.03<|t|<1Ge2, with at least two jets with transverse momentum pT>40Ge, and pseudorapidity | η| < 4.4 , is 21.7±0.9(stat)-3.3+3.0(syst)±0.9(lumi)nb. The ratio of the single-diffractive to inclusive dijet yields, normalised per unit of ξ, is presented as a function of x, the longitudinal momentum fraction of the proton carried by the struck parton. The ratio in the kinematic region defined above, for x values in the range - 2.9 ≤ log 10x≤ - 1.6 , is R=(σjjpX/Δξ)/σjj=0.025±0.001(stat)±0.003(syst), where σjjpX and σjj are the single-diffractive and inclusive dijet cross sections, respectively. The results are compared with predictions from models of diffractive and nondiffractive interactions. Monte Carlo predictions based on the HERA diffractive parton distribution functions agree well with the data when corrected for the effect of soft rescattering between the spectator partons. © 2020, CERN for the benefit of the CMS and TOTEM collaborations

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton–proton collisions at an energy of s=13TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb-1. A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯. © 2020, The Author(s)