Resident Cellular Components of the Human Lung Current Knowledge and Goals for Research on Cell Phenotyping and Function

The purpose of the workshop was to identify still obscure or novel cellular components of the lung, to determine cell function in lung development and in health that impacts on disease, and to decide promising avenues for future research to extract and phenotype these cells. Since robust technologies are now available to identify, sort, purify, culture, and phenotype cells, progress is now within sight to unravel the origins and functional capabilities of lung cells in developmental stages and in disease. The Workshop's agenda was to first discuss the lung's embryologic development, including progenitor and stem cells, and then assess the functional and structural cells in three main compartments of the lung: (1) airway cells in bronchial and bronchiolar epithelium and bronchial glands (basal, secretory, ciliated, Clara, and neuroendocrine cells); (2) alveolar unit cells (Type 1 cells, Type 2 cells, and fibroblasts in the interstitium); and (3) pulmonary vascular cells (endothelial cells from different vascular structures, smooth muscle cells, and adventitial fibroblasts). The main recommendations were to: (1) characterize with better cell markers, both surface and nonsurface, the various cells within the lung, including progenitor cells and stem cells; (2) obtain more knowledge about gene expression in specific cell types in health and disease, which will provide insights into biological and pathologic processes; (3) develop more methodologies for cell culture, isolation, sorting, co-culture, and immortalization; and (4) promote tissue banks to facilitate the procurement of tissue from normal and from diseased lung for analysis at all levels

Riociguat treatment in patients with chronic thromboembolic pulmonary hypertension: Final safety data from the EXPERT registry

Objective: The soluble guanylate cyclase stimulator riociguat is approved for the treatment of adult patients with pulmonary arterial hypertension (PAH) and inoperable or persistent/recurrent chronic thromboembolic pulmonary hypertension (CTEPH) following Phase

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Software performance of the ATLAS track reconstruction for LHC run 3

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pileup) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60 pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two