To investigate whether inflammatory indices, including the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), product of platelet and neutrophil count (PPN), and lymphocyte-to-monocyte ratio (LMR), correlate with chronic obstructive pulmonary disease (COPD). This was a cross-sectional study from the National Health and Nutrition Examination Survey (NHANES) database 2007–2018. The SII, NLR, PLR, PPN and LMR were calculated based on blood cell counts and were log2-transformed. COPD was diagnosed via a questionnaire or spirometry examination. Multivariate logistic regression, sensitivity analysis, subgroup analyses, and interaction tests were performed to evaluate the relationships. 23,875 participants, including 1000 COPD patients (453 diagnosed via spirometry examination, 547 diagnosed via a questionnaire), were enrolled in this study. Positive associations were observed between SII (OR 1.231, 95 % CI 1.081,1.401), NLR (OR 1.223, 95 % CI 1.064,1.405), PLR (OR 1.325, 95 % CI 1.086,1.617), PPN (OR 1.157, 95 % CI 1.031,1.298) and COPD, while a negative association was obtained between LMR and COPD (OR 0.794, 95 % CI 0.666,0.948) after covariate adjustments. When divided COPD patients into spirometry-based and questionnaire-based, only SII (OR 1.310, 95%CI 1.122,1.529), PLR (OR 1.669, 95%CI 1.272,2.191) and PPN (OR 1.218, 95%CI 1.050,1.412) significantly correlated with spirometry-based COPD, while only NLR (OR 1.303, 95%CI 1.055,1.609) and LMR (OR 0.524, 95%CI 0.406,0.677) significantly correlated with questionnaire-based COPD after covariate adjustments. Significant associations are observed between different inflammation indices and COPD. Heterogeneity exists between spirometry-based and questionnaire-based COPD patients. Future studies are needed to verify the results.

As a novel kind of non‐coding RNA, circular RNAs (circRNAs) were involved in various biological processes. However, the role of circRNAs in the developmental process of chronic obstructive pulmonary disease (COPD) is still unclear. In the present study, by using a cell model of COPD in primary human small airway epithelial cells (HSAECs) treated with or without cigarette smoke extract (CSE), we uncovered 4,379 previously unknown circRNAs in human cells and 903 smoke‐specific circRNAs, with the help of RNA‐sequencing and bioinformatic analysis. Moreover, 3,872 up‐ and 4,425 down‐regulated mRNAs were also identified under CSE stimulation. Furthermore, a putative circRNA‐microRNA‐mRNA network was constructed for in‐depth mechanism exploration, which indicated that differentially expressed circRNAs could influence expression of some key genes that participate in response to pentose phosphate pathway, ATP‐binding cassette (ABC) transporters, glycosaminoglycan biosynthesis pathway and cancer‐related pathways. Our research indicated that cigarette smoke had an influence on the biogenesis of circRNAs and mRNAs. CircRNAs might be involved in the response to CSE in COPD through the circRNA‐mediated ceRNA networks.

This study investigated whether the mitochondrial‐targeted peptide SS‐31 can protect against cigarette smoke‐ (CS‐) induced airway inflammation and oxidative stress in vitro and in vivo. Mice were exposed to CS for 4 weeks to establish a CS‐induced airway inflammation model, and those in the experimental group were pretreated with SS‐31 1 h before CS exposure. Pathologic changes and oxidative stress in lung tissue, inflammatory cell counts, and proinflammatory cytokine levels in bronchoalveolar lavage fluid (BALF) were examined. The mechanistic basis for the effects of SS‐31 on CS extract‐ (CSE‐) induced airway inflammation and oxidative stress was investigated using BEAS‐2B bronchial epithelial cells and by RNA sequencing and western blot analysis of lung tissues. SS‐31 attenuated CS‐induced inflammatory injury of the airway and reduced total cell, neutrophil, and macrophage counts and tumor necrosis factor‐ (TNF‐) α, interleukin‐ (IL‐) 6, and matrix metalloproteinase (MMP) 9 levels in BALF. SS‐31 also attenuated CS‐induced oxidative stress by decreasing malondialdehyde (MDA) and myeloperoxidase (MPO) activities and increasing that of superoxide dismutase (SOD). It also reversed CS‐induced changes in the expression of mitochondrial fission protein (MFF) and optic atrophy (OPA) 1 and reduced the amount of cytochrome c released into the cytosol. Pretreatment with SS‐31 normalized TNF‐α, IL‐6, and MMP9 expression, MDA and SOD activities, and ROS generation in CSE‐treated BEAS‐2B cells and reversed the changes in MFF and OPA1 expression. RNA sequencing and western blot analysis showed that SS‐31 inhibited CS‐induced activation of the mitogen‐activated protein kinase (MAPK) signaling pathway in vitro and in vivo. Thus, SS‐31 alleviates CS‐induced airway inflammation and oxidative stress via modulation of mitochondrial function and regulation of MAPK signaling and thus has therapeutic potential for the treatment of airway disorders caused by smoking.

Background/Aims: Recently, many studies have demonstrated that various tumor-associated autoantibodies have been detected in early stages of lung cancer. Therefore, we conducted a meta-analysis to comprehensively evaluate available evidence on the diagnostic value of autoantibodies against tumor-associated antigens in lung cancer. Methods: We systematically searched PubMed, Scopus, Web of Science and other databases through 23 March 2018. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. We used the bivariate mixed-effect models to calculate pooled values of sensitivity, specificity, positive likelihood ratios, negative likelihood ratios, diagnostic odds ratios and associated 95% confidence intervals. Summary receiver operating characteristic (SROC) curves were used to summarize overall test performance. Deek’s funnel plot was used to detect publication bias. Results: Review of 468 candidate articles identified fifty-three articles with a total of 11,515 patients for qualitative review and meta-analysis. Pooled sensitivity, specificity and area under the SROC curve were as follows for tumor-associated autoantibodies against the following proteins: p53, 0.19, 0.98, 0.82; NY-ESO-1, 0.17, 0.98, 0.90; Survivin, 0.19, 0.99, 0.96; c-myc, 0.14, 0.98, 0.45; Cyclin B1, 0.18, 0.98, 0.91; GBU4-5, 0.07, 0.98, 0.91; CAGE, 0.14, 0.98, 0.90; p16, 0.08, 0.97, 0.91; SOX2, 0.14, 0.99, 0.93; and HuD, 0.17, 0.99, 0.82. Conclusion: Each tumor-associated autoantibody on its own showed excellent diagnostic specificity for lung cancer but inadequate sensitivity. Our results suggest that combinations or panels of tumor-associated autoantibodies may provide better sensitivity for diagnosing lung cancer, and the diagnostic accuracy of tumor-associated autoantibodies should be validated in more studies.