Human cells release nano-sized vesicles called exosomes, containing mRNA, miRNA and specific proteins. Exosomes from one cell can be taken up by another cell, which is a recently discovered cell-to-cell communication mechanism. Also, exosomes can be taken up by different types of cancer cells, but the potential functional effects of mast cell exosomes on tumor cells remain unknown. Exosomes were isolated from the human mast cell line, HMC-1, and uptake of PKH67-labelled exosomes by the lung epithelial cell line, A549, was examined using flow cytometry and fluorescence microscopy. The RNA cargo of the exosomes was analyzed with a Bioanalyzer and absence or presence of the c-KIT mRNA was determined by RT-PCR. The cell proliferation was determined in a BrdU incorporation assay, and proteins in the KIT-SCF signaling pathway were detected by Western blot. Our result demonstrates that exosomes from mast cells can be taken up by lung cancer cells. Furthermore, HMC-1 exosomes contain and transfer KIT protein, but not the c-KIT mRNA to A549 cells and subsequently activate KIT-SCF signal transduction, which increase cyclin D1 expression and accelerate the proliferation in the human lung adenocarcinoma cells. Our results indicate that exosomes can transfer KIT as a protein to tumor cells, which can affect recipient cell signaling events through receptor-ligand interactions.

Airway epithelial cells (AECs) and mast cells (MCs) are pivotal initiators and amplifiers of airway inflammation, orchestrating a dynamic crosstalk that drives pathological hyperreactivity in respiratory diseases. AECs, as the frontline barrier, detect pathogens and allergens, releasing cytokines (e.g., IL-33, TSLP) and chemokines to activate neighboring MCs. Conversely, MC-derived proteases (tryptase, chymase) and mediators (histamine, leukotrienes) disrupt epithelial junctions (e.g., E-cadherin, occludin), exacerbating barrier dysfunction and perpetuating cycles of inflammation. This reciprocal interaction establishes a molecular hub for ‘hyperinflammation’ in asthma, chronic obstructive pulmonary disease (COPD), and viral infections, while also contributing to pathological processes such as airway remodeling, fibrosis, and epithelial-mesenchymal transition (EMT). Therefore, elucidating the synergistic mechanisms underlying AEC-MC crosstalk is critically important. This review synthesizes emerging insights into AEC-MC crosstalk, emphasizing context-specific mechanisms in viral, allergic, and chronic inflammatory settings, and provide suggestions for future research directions.

Preeclampsia (PE) affects 2–4% of pregnancies, and early detection and intervention can reduce its incidence. Dysregulation of the maternal immune response and red blood cells (RBCs) are key to its development, although early alterations remain unclear. This study analyzed data from 17,955 pregnant women across two centers to explore the relationships among inflammatory markers, RBC indices, and PE via multivariate logistic regression and restricted cubic splines (RCSs). Machine learning integrated inflammatory markers, RBC indices, and maternal risk factors to predict PE risk at 14 weeks, as validated by receiver operating characteristic (ROC) curve analysis. After adjusting for confounders, the lymphocyte (LYMPH) count (OR = 1.27, 95% CI: 1.05–1.53, P = 0.013), monocyte (MONO) count (OR = 2.57, 95% CI: 1.31–5.03, P = 0.006), systemic inflammatory response index (SIRI) (OR = 1.11, 95% CI: 1.01–1.21, P = 0.032), and systemic immune inflammatory index (SII) (OR = 1.01, 95% CI: 1.01–1.01, P = 0.002) were identified as significant risk factors for PE. Nonlinear associations between white blood cell (WBC) count, neutrophil (NEUT) count, platelet (PLT) count, RBC count, and hemoglobin (HGB) and PE were observed via RCS (nonlinear P < 0.05). Further analysis revealed threshold effects for WBC (P = 0.034), with an inflection point at 8.44. Below 8.44, no significant association was found (OR = 0.92, P = 0.307), but above 8.44, each unit increase was linked to a 0.14-fold rise in PE risk (OR = 1.14, P < 0.001). Similar threshold effects were found for the PLT, RBC, and HGB (P < 0.001). A prediction model based on inflammatory markers, RBC indices, and maternal risk factors achieved high performance (ROC = 0.82). LYMPH, MONO, SIRI, and SII were linearly associated with PE, whereas WBC, NEUT, PLT, RBC, and HGB showed nonlinear associations with threshold effects. Early prediction using these indicators is a cost-effective strategy for PE prevention.

Non-pharmaceutical interventions (NPIs) implemented during the COVID-19 pandemic had a significant impact on the epidemiology of respiratory pathogens. Following the relaxation of these measures, a notable increase in Mycoplasma pneumoniae (Mp) pneumonia incidence among children was observed. To comprehensively analyze the impact of NPIs on the patterns of Mp infections in children, we assessed changes in the epidemiology and clinical features of Mp infections in Songjiang District, Shanghai, before, during, and after the pandemic. A total of 6,050 hospitalized children with community-acquired pneumonia (CAP) from January 2017 to December 2024 were included. Annual Mp epidemiology was analyzed from 2017 to 2024. To assess NPI-specific effects, three comparative phases were defined: Before (June 2017–May 2019, pre-pandemic), During (June 2020–May 2022, active pandemic with NPIs), and After (June 2022–May 2024, post-NPIs). Epidemiological characteristics, clinical features, and laboratory findings were systematically compared across these phases. From 2017 to 2024, the number of hospitalized CAP cases significantly decreased from 2020 to 2022, with an overall Mp positivity rate of 43.16%. Annual Mp positivity rate peaked at 56.32% in 2022 versus 30.70% in 2020. Intergroup comparisons revealed that the After group exhibited the highest Mp positivity rate (56.03%), significantly exceeding both the Before (28.59%) and During (41.63%) groups. Notably, the After group exhibited significantly lower white blood cell count (WBC) and C-reactive protein (CRP), alongside elevated platelet count (PLT) and alanine aminotransferase (ALT). The proportion of patients with low Mp antibody titers (1:80) was significantly higher in the During group, whereas high-titer categories (1:320 and >1:640) predominated in the After group. NPIs during the COVID-19 pandemic significantly altered the epidemiology and clinical features of Mp infections in children in Songjiang District, Shanghai. IMPORTANCE: This study examines the effects of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic on the epidemiology of Mycoplasma pneumoniae (Mp) infections in children. By analyzing data from over 6,000 hospitalized children with community-acquired pneumonia, the research reveals a significant change in Mp infection patterns, with a marked increase in positivity rates after NPIs were relaxed. The findings indicate a shift in the affected demographic, with more school-age children presenting with Mp infections, as well as variations in clinical features such as different laboratory results. This research provides valuable insights for healthcare professionals in understanding the implications of NPIs on respiratory infections in children, guiding future treatment approaches and public health strategies. It represents a meaningful contribution to the ongoing evaluation of pediatric health in a post-pandemic context.

To analyze the positive rate and genotype distribution of human papillomavirus (HPV) infection in Yangpu District, Shanghai, and to provide a scientific basis for the prevention and treatment of cervical cancer and related diseases. A retrospective analysis was conducted on HPV genotyping data from 19,142 outpatients, inpatients, and health examinees at Shanghai Shidong Hospital from 2020 to 2024. Overall infection rate, genotype distribution, age-specific positivity, and annual trends were evaluated. Among 19,142 specimens, 4,421 tested positive for HPV, yielding a total positive rate of 23.10%. The top five prevalent genotypes were HPV-52 (21.72%), HPV-53 (11.94%), HPV-58 (10.19%), HPV-51 (8.02%), and HPV-39 (6.86%). Dominant genotypes varied across years. Age-specific infection rates followed an approximate U-shaped curve, with peaks in the ≤ 20-year group (57.69%) and the 61–70-year group (29.72%). Among mixed infections (28.70% of positives), single infections predominated (71.30%). The most common co-infection combinations were HPV-52 + HPV-53 and HPV-52 + HPV-58. High-risk age groups for HPV infection were 31–40, 51–60, and 61–70 years. The HPV infection rate in Yangpu District, Shanghai, was 23.10%, primarily driven by single-genotype infections. HPV-52, -53, and − 58 were the dominant genotypes, with significant age-specific variations. These findings underscore the need for enhanced HPV vaccination promotion and targeted preventive strategies.