Microbiota as an integral component of human body is actively investigated, including by massively parallel sequencing. However, microbiomes of lungs and sinuses have become the object of scientific attention only in the last decade. For patients with cystic fibrosis, monitoring the state of respiratory tract microorganisms is essential for maintaining lung function. Here, we studied the role of sinuses and polyps in the formation of respiratory tract microbiome. We identified Proteobacteria in the sinuses and samples from the lower respiratory tract (even in childhood). In some cases, they were accompanied by potentially dangerous basidiomycetes. The presence of polyps did not affect formation of the sinus microbiome. Proteobacteria are decisive in reducing the biodiversity of lung and sinus microbiomes, which correlated with the worsening of the lung function indicators. Soft mutations in the CFTR gene contribute to the formation of safer microbiome even in heterozygotes with class I mutations.
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http://dx.doi.org/10.1134/S0006297920010010 | DOI Listing |
Fetal Pediatr Pathol
January 2025
Lauren V. Ackerman Laboratory of Surgical Pathology, Department of Pathology and Immunology, St. Louis, MO, USA.
, a gram-negative bacillus, has varied clinical manifestations with septicemia as the most lethal. PA infection is usually regarded as opportunistic and often nosocomial. We present a case of a "healthy" pediatric patient presenting with upper respiratory symptoms who rapidly deteriorated.
View Article and Find Full Text PDFBackground And Aims: Hematopoietic stem cell transplantation (HSCT) is a key therapeutic approach for pediatric patients with hematologic and non-hematologic disorders. However, post-transplant pulmonary complications remain a significant cause of morbidity and mortality. Pulmonary Function Tests (PFTs) are essential for the early detection of pulmonary dysfunction, yet their application in pediatric HSCT recipients has yielded inconsistent results.
View Article and Find Full Text PDFFront Immunol
January 2025
Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China.
Background: Respiratory syncytial virus (RSV) is a major cause of severe health problems in newborns and young children. The protective role and limitations of serum maternal RSV antibodies in infants under 3 months remain controversial.
Methods: A two-center prospective study from 2020 to 2023 recruited infants (n=286) admitted to the respiratory departments of two children's hospitals in southwestern and southeastern China during RSV epidemic.
Front Immunol
January 2025
State Key Laboratory of Traditional Chinese Medicine Syndrome, Department of Neurology, Guangdong Provincial Academy of Chinese Medical Sciences, Guangdong Provincial Hospital of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Background: A stable and reproducible experimental bacterial pneumonia model postintracerebral hemorrhage (ICH) is necessary to help investigating the pathogenesis and novel treatments of Stroke-associated pneumonia (SAP).
Aim: To establish a Gram-negative bacterial pneumonia-complicating ICH rat model and an acute lung injury (ALI)-complicating ICH rat model.
Methods: We established two standardized models of post-ICH pneumonia by nasal inoculation with () or intratracheal inoculation with lipopolysaccharide (LPS).
Front Med (Lausanne)
January 2025
Department of Respiratory Medicine, Reference Centre for Rare Pulmonary Diseases, APHP, Hôpital Avicenne, INSERM U 1272, Université Sorbonne Paris-Nord, Bobigny, France.
LAM is a rare multi-cystic lung disease for which treatment with sirolimus is indicated in cases of moderate or severe lung disease or declining lung function. The aim of this study was to describe patients treated with sirolimus for LAM and their outcomes. This retrospective observational study was based on data from the French national health insurance data system (SNDS).
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