Chronic obstructive pulmonary disease (COPD) is a common respiratory disease characterized by irreversible progressive airflow limitation, often manifested by persistent cough, sputum production and other respiratory symptoms that pose a serious threat to human health and affect the quality of life of patients. The disease is associated with chronic inflammation, which is associated with the onset and progression of COPD, but anti-inflammatory therapy is not first-line treatment. Inflammation has multiple manifestations and phenotypes, and this heterogeneity reveals different patterns of inflammation, making treatment difficult. This paper aims to explore the direction of more effective anti-inflammatory treatment by analyzing the nature of inflammation and the molecular mechanism of disease occurrence and development in COPD patients, and to provide new ideas for the treatment of COPD patients.

Background: Recently, Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome virus 2 (SARS-CoV-2), has affected more than 200 countries and lead to enormous losses. This study systematically reviews the application of Artificial Intelligence (AI) techniques in COVID-19, especially for diagnosis, estimation of epidemic trends, prognosis, and exploration of effective and safe drugs and vaccines; and discusses the potential limitations.Methods: We report this systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched PubMed, Embase and the Cochrane Library from inception to 19 September 2020 for published studies of AI applications in COVID-19. We used PROBAST (prediction model risk of bias assessment tool) to assess the quality of literature related to the diagnosis and prognosis of COVID-19. We registered the protocol (PROSPERO CRD42020211555).Results: We included 78 studies: 46 articles discussed AI-assisted diagnosis for COVID-19 with total accuracy of 70.00 to 99.92%, sensitivity of 73.00 to 100.00%, specificity of 25 to 100.00%, and area under the curve of 0.732 to 1.000. Fourteen articles evaluated prognosis based on clinical characteristics at hospital admission, such as clinical, laboratory and radiological characteristics, reaching accuracy of 74.4 to 95.20%, sensitivity of 72.8 to 98.00%, specificity of 55 to 96.87% and AUC of 0.66 to 0.997 in predicting critical COVID-19. Nine articles used AI models to predict the epidemic of the COVID-19, such as epidemic peak, infection rate, number of infected cases, transmission laws, and development trend. Eight articles used AI to explore potential effective drugs, primarily through drug repurposing and drug development. Finally, 1 article predicted vaccine targets that have the potential to develop COVID-19 vaccines.Conclusions: In this review, we have shown that AI achieved high performance in diagnosis, prognosis evaluation, epidemic prediction and drug discovery for COVID-19. AI has the potential to enhance significantly existing medical and healthcare system efficiency during the COVID-19 pandemic.

Lung macrophages constitute the first line of defense against airborne particles and microbes and are key to maintaining pulmonary immune homeostasis. There is increasing evidence suggesting that macrophages also participate in the pathogenesis of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS), including the modulation of inflammatory responses and the repair of damaged lung tissues. The diversity of their functions may be attributed to their polarized states. Classically activated or inflammatory (M1) macrophages and alternatively activated or anti-inflammatory (M2) macrophages are the two main polarized macrophage phenotypes. The precise regulatory mechanism of macrophage polarization is a complex process that is not completely understood. A growing body of literature on immunometabolism has demonstrated the essential role of immunometabolism and its metabolic intermediates in macrophage polarization. In this review, we summarize macrophage polarization phenotypes, the role of immunometabolism, and its metabolic intermediates in macrophage polarization and ALI/ARDS, which may represent a new target and therapeutic direction.

CD26/Dipeptidyl peptidase 4 (DPP4) is a type II transmembrane glycoprotein that is widely expressed in various organs and cells. It can also exist in body fluids in a soluble form. DPP4 participates in various physiological and pathological processes by regulating energy metabolism, inflammation, and immune function. DPP4 inhibitors have been approved by the Food and Drug Administration (FDA) for the treatment of type 2 diabetes mellitus. More evidence has shown the role of DPP4 in the pathogenesis of lung diseases, since it is highly expressed in the lung parenchyma and the surface of the epithelium, vascular endothelium, and fibroblasts of human bronchi. It is a potential biomarker and therapeutic target for various lung diseases. During the coronavirus disease-19 (COVID-19) global pandemic, DPP4 was found to be an important marker that may play a significant role in disease progression. Some clinical trials on DPP4 inhibitors in COVID-19 are ongoing. DPP4 also affects other infectious respiratory diseases such as Middle East respiratory syndrome and non-infectious lung diseases such as pulmonary fibrosis, lung cancer, chronic obstructive pulmonary disease (COPD), and asthma. This review aims to summarize the roles of DPP4 and its inhibitors in infectious lung diseases and non-infectious diseases to provide new insights for clinical physicians.

Purpose: A systematic review and meta-analysis was conducted to synthesize the available data from clinical trials and assess the safety issues of tirzepatide (pancreatitis and gallbladder or biliary disease) in type 2 diabetes (T2D) and obesity.Methods: A systematic search was conducted in three electronic databases, namely Embase, PubMed, and the Cochrane Library, up until March 1, 2023, to identify randomized controlled trials (RCTs) comparing tirzepatide to either placebo or active hypoglycemic drugs in individuals with T2D and obesity. Heterogeneity was assessed using the I2 value and Cochran’s Q test, and a fixed effects model was employed to estimate the safety profile of tirzepatide. The safety outcomes of interest, including pancreatitis, the composite of gallbladder or biliary diseases, cholecystitis, and cholelithiasis and biliary diseases, were evaluated. (The composite of gallbladder or biliary diseases incorporated cholelithiasis, cholecystitis, other gallbladder disorders, and biliary diseases.)Results: A total of nine trials with 9871 participants (6828 in the tirzepatide group and 3043 in the control group) that met the pre-specified criteria were included. When compared to all control groups consisting of basal insulin (glargine or degludec), selective GLP1-RA (dulaglutide or semaglutide once weekly), and placebo, an increased risk of pancreatitis was not found to be significantly associated with tirzepatide (RR 1.46, [95% CI] 0.59 to 3.61; I2 = 0.0%, p = 0.436). For gallbladder or biliary disease, the composite of gallbladder or biliary disease was significantly associated with tirzepatide compared with placebo or basal insulin (RR 1.97, [95% CI] 1.14 to 3.42; I2 = 0.0%, p = 0.558), but not with the risk of cholelithiasis, cholecystitis or biliary diseases.Conclusion: Based on the currently available data, tirzepatide appears to be safe regarding the risk of pancreatitis. However, the increased risk of the composite outcome of gallbladder or biliary diseases observed in RCTs warrants further attention from physicians in clinical practice.Systematic review registration: https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023412400.

Idiopathic pulmonary fibrosis (IPF) is a progressive, lethal, and chronic lung disease. There are no effective drug therapies for IPF. Hyperoside, a flavonoid glycoside, has been proven to have anti-inflammatory, anti-fibrosis, antioxidant, and anti-cancer effects. The aim of this study was to explore the role of hyperoside in bleomycin-induced pulmonary fibrosis development in mice. We established the pulmonary fibrosis model by a single intratracheal aerosol injection of bleomycin. Seven days after the bleomycin treatment, the mice were intraperitoneally administered with hyperoside for 14 days. We found that hyperoside treatment ameliorated fibrotic pathological changes and collagen deposition in the lungs of mice with bleomycin-induced pulmonary fibrosis. Hyperoside treatment also reduced the levels of MDA, TNF-α, and IL-6 and increased the activity of SOD. In addition, hyperoside might inhibit the epithelial-mesenchymal transition (EMT) via the AKT/GSK3β pathway. Based on these findings, hyperoside attenuated pulmonary fibrosis development by inhibiting oxidative stress, inflammation, and EMT in the lung tissues of mice with pulmonary fibrosis. Therefore, hyperoside might be a promising candidate drug for the treatment of pulmonary fibrosis.