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The triggering receptor expressed by myeloid cells-1 (TREM-1) plays an important role in infectious and autoimmune diseases but how it contributes to ventilation-induced lung injury (VILI) and inflammation is unclear. Here, we examine the possibility that TREM-1 activates signaling dependent on Toll-like receptor 4 (TLR4), myeloid differentiation factor 88 (Myd88) and nuclear factor (NF)-κB, which leads in turn to VILI. In a mouse model of VILI, which we validated based on lung edema and histopathology as well as cytokine levels, we examine mRNA and protein levels of TREM-1, TLR4, MyD88, NF-κB and its inhibitory protein I-κB in animals subjected to ventilation at normal or high tidal volume. The extent of lung edema, injury and inflammation were higher in the high tidal volume animals, as were the expression levels of all proteins examined. Treatment with TREM-1 agonist aggravated these effects, whereas treatment with TREM-1 antagonist attenuated them. Our results suggest that aggravation of VILI by TREM-1 in mice may be associated with TLR4-MyD88-NF-κB-dependent signaling.

Introduction: Lung cancer the most prevalent cause of cancer-related deaths, and current therapies lack sufficient specificity and efficacy. This study developed an injectable thermosensitive hydrogel harboring hollow copper sulfide nanoparticles and β-lapachone (Lap) (CLH) for lung tumor treatment.Methods: The hydrogel-encapsulated CLH system can remotely control the release of copper ions (Cu2+) and drugs using photothermal effects for non-invasive controlled-release drug delivery in tumor therapy. The released Cu2+ consumes the overexpressed GSH in TME and the generated Cu+ further exploits the TME characteristics to initiate nanocatalytic reactions for generating highly toxic hydroxyl radicals. In addition, in cancer cells overexpressing Nicotinamide adenine dinucleotide (phosphate): quinone oxidoreductase 1 (NQO1), Lap can catalyze the generation of hydrogen peroxide (H2O2) through futile redox cycles. H2O2 is further converted into highly toxic hydroxyl radicals via the Fenton-like reaction, leading to a burst of reactive oxygen species in TME, which further enhances the therapeutic effect of chemokines.Results: Analysis of the antitumor efficacy in a subcutaneous A549 lung tumor model mice showed a significant delay in tumor growth and no systemic toxicity was detected.Discussion: In conclusion, we have established a CLH nanodrug platform that enables efficient lung tumor therapy through combined photothermal/chemodynamic therapy (CDT) treatment and self-supplying H2O2 to achieve cascade catalysis, leading to explosive amplification of oxidative stress.

Effective radiosensitizers are urgently needed due to the serious negative effects that high radiation doses might have. We created an integrated nano-system (Cuhemin-Au) made of Cuhemin nanosheets and Au nanoparticles...

Background Breast cancer is a malignant tumour that seriously threatens women’s life and health and exhibits high inter-individual heterogeneity, emphasising the need for more in-depth research on its pathogenesis. While internal 7-methylguanosine (m7G) modifications affect RNA processing and function and are believed to be involved in human diseases, little is currently known about the role of m7G modification in breast cancer. Methods and Results We elucidated the expression, copy number variation incidence and prognostic value of 24 m7G-related genes (m7GRGs) in breast cancer. Subsequently, based on the expression of these 24 m7GRGs, consensus clustering was used to divide tumour samples from the TCGA-BRCA dataset into four subtypes based on significant differences in their immune cell infiltration and stromal scores. Differentially expressed genes between subtypes were mainly enriched in immune-related pathways such as ‘Ribosome’, ‘TNF signalling pathway’ and ‘Salmonella infection’. Support vector machines and multivariate Cox regression analysis were applied based on these 24 m7GRGs, and four m7GRGs—AGO2, EIF4E3, DPCS and EIF4E—were identified for constructing the prediction model. An ROC curve indicated that a nomogram model based on the risk model and clinical factors had strong ability to predict the prognosis of breast cancer. The prognoses of patients in the high- and low-TMB groups were significantly different (p = 0.03). Moreover, the four-gene signature was able to predict the response to chemotherapy. Conclusions In conclusion, we identified four different subtypes of breast cancer with significant differences in the immune microenvironment and pathways. We elucidated prognostic biomarkers associated with breast cancer and constructed a prognostic model involving four m7GRGs. In addition, we predicted the candidate drugs related to breast cancer based on the prognosis model.