Mangroves are one of the blue carbon ecosystems. However, greenhouse gas emissions from mangrove soils may reduce the capacity of carbon storage in these systems. In this study, methane (CH4) fluxes and soil properties of the top 10 cm layer were determined in subtropical (Kandelia obovata) and tropical (Avicennia marina) mangrove ecosystems of Taiwan for a complete seasonal cycle. Our results demonstrate that CH4 emissions in mangroves cannot be neglected when constructing the carbon budgets and estimating the carbon storage capacity. CH4 fluxes were significantly higher in summer than in winter in the Avicennia mangroves. However, no seasonal variation in CH4 flux was observed in the Kandelia mangroves. CH4 fluxes were significantly higher in the mangrove soils of Avicennia than in the adjoining mudflats; this trend, however, was not necessarily recapitulated at Kandelia. The results of multiple regression analyses show that soil water and organic matter content were the main factors regulating the CH4 fluxes in the Kandelia mangroves. However, none of the soil parameters assessed show a significant influence on the CH4 fluxes in the Avicennia mangroves. Since pneumatophores can transport CH4 from anaerobic deep soils, this study suggests that the pneumatophores of Avicennia marina played a more important role than soil properties in affecting soil CH4 fluxes. Our results show that different mangrove tree species and related root structures may affect greenhouse gas emissions from the soils.

Personalized genetic profiling has focused on improving treatment efficacy and predicting risk stratification by identifying mutated genes and selecting targeted agents according to genetic testing. Therefore, we evaluated the role of genetic profiling and tumor mutation burden (TMB) using next-generation sequencing in patients with head and neck squamous cell carcinoma (HNSC). The relapse mutation signature (RMS) and chromatin remodeling mutation signature (CRMS) were explored to predict the risk of relapse in patients with HNSC treated with concurrent chemoradiotherapy (CCRT) with platinum-based chemotherapy. Patients in the high RMS and CRMS groups showed significantly shorter relapse-free survival than those in the low RMS and CRMS groups, respectively (p < 0.001 and p = 0.006). Multivariate Cox regression analysis showed that extranodal extension, CCRT response, and three somatic mutation profiles (TMB, RMS, and CRMS) were independent risk predictors for HNSC relapse. The predictive nomogram showed satisfactory performance in predicting relapse-free survival in patients with HNSC treated with CCRT.

The aim of this single-center case-control study is to investigate the feasibility and accuracy of oral cancer protein risk stratification (OCPRS) to analyze the risk of cancer progression. All patients diagnosed with oral cancer in Taiwan, between 2012 and 2014, and who underwent surgical intervention were selected for the study. The tissue was further processed for immunohistochemistry (IHC) for 21 target proteins. Analyses were performed using the results of IHC staining, clinicopathological characteristics, and survival outcomes. Novel stratifications with a hierarchical clustering approach and combinations were applied using the Cox proportional hazard regression model. Of the 163 participants recruited, 102 patients were analyzed, and OCPRS successfully identified patients with different progression-free survival (PFS) profiles in high-risk (53 subjects) versus low-risk (49 subjects) groups (p = 0.012). OCPRS was composed of cytoplasmic PLK1, phosphoMet, and SGK2 IHC staining. After controlling for the influence of clinicopathological features, high-risk patients were 2.33 times more likely to experience cancer progression than low-risk patients (p = 0.020). In the multivariate model, patients with extranodal extension (HR = 2.66, p = 0.045) demonstrated a significantly increased risk for disease progression. Risk stratification with OCPRS provided distinct PFS groups for patients with oral cancer after surgical intervention. OCPRS appears suitable for routine clinical use for progression and prognosis estimation.