Asthma is characterized by reversible airflow obstruction, bronchial hyper-reactivity, and chronic airway remodeling ( Al-Muhsen et al., 2011). Pulmonary macrophages have been implicated in asthmatic inflammation ( Lee et al., 2015; Qian et al., 2015). The p38 mitogen-activated protein kinase (MAPK) plays an essential role in inflammation, but its role in asthma has not been determined ( Kim et al., 2008). Here, our data show that macrophage-specific p38α MAPK-deficient mice displayed attenuated asthmatic inflammation in response to three allergens (dust mite, ragweed, and Aspergillus; DRA). Furthermore, we found that the protective effect was strongly associated with a reduction in the alternatively activated macrophage (AAM) polarization in vivo and in vitro. Taken together, our data indicate that p38α MAPK in macrophages contributes to AAM polarization and could be a therapeutic target for asthma.

Pancreatic cancer is a highly fatal disease and an increasing common cause of cancer mortality. Mounting evidence now indicates that molecular heterogeneity in pancreatic cancer significantly impacts its clinical features. However, the dynamic nature of gene expression pattern makes it difficult to rely solely on gene expression alterations to estimate disease status. By contrast, biological networks tend to be more stable over time under different situations. In this study, we used a gene interaction network from a new point of view to explore the subtypes of pancreatic cancer based on individual-specific edge perturbations calculated by relative gene expression value. Our study shows that pancreatic cancer patients from the TCGA database could be separated into four subtypes based on gene interaction perturbations at the individual level. The new network-based subtypes of pancreatic cancer exhibited substantial heterogeneity in many aspects, including prognosis, phenotypic traits, genetic mutations, the abundance of infiltrating immune cell, and predictive therapeutic efficacy (chemosensitivity and immunotherapy efficacy). The new network-based subtypes were closely related to previous reported molecular subtypes of pancreatic cancer. This work helps us to better understand the heterogeneity and mechanisms of pancreatic cancer from a network perspective.