Development and validation of a pyroptosis-related prognostic signature associated with osteosarcoma metastasis and immune infiltration.

Pyroptosis is a programmed cell death, which has garnered increasing attention because it relates to the immune and therapy response. However, few studies focus on the application of pyroptosis-related genes (PRGs) in predicting osteosarcoma (OS) patients' prognoses. In this study, the gene expression and clinical information of OS patients were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Based on these PRGs and unsupervised clustering analysis, all OS samples can be classified into 2 clusters. The 8 key differential expressions for PRGs (LAG3, ITGAM, CCL2, TLR4, IL2RA, PTPRC, FCGR2B, and CD5) were established through the univariate Cox regression and utilized to calculate the risk score of all samples. According to the 8-gene signature, OS samples can be divided into high and low-risk groups and correlation analysis can be performed using immune cell infiltration and immune checkpoints. Finally, we developed a nomogram to improve the PRG-predictive model in clinical application. We verified the predictive performance using receiver operating characteristic (ROC) and calibration curves. There were significant differences in survival, immune cell infiltration and immune checkpoints between the low and high-risk groups. A nomogram was developed with clinical indicators and the risk scores were effective in predicting the prognosis of patients with OS. In this study, a prognostic model was constructed based on 8 PRGs were proved to be independent prognostic factors of OS and associated with tumor immune microenvironment. These 8 prognostic genes were involved in OS development and may serve as new targets for developing therapeutic drugs.

Development and validation of two redox-related genes associated with prognosis and immune microenvironment in endometrial carcinoma.

In recent studies, the tumourigenesis and development of endometrial carcinoma (EC) have been correlated significantly with redox. We aimed to develop and validate a redox-related prognostic model of patients with EC to predict the prognosis and the efficacy of immunotherapy. We downloaded gene expression profiles and clinical information of patients with EC from the Cancer Genome Atlas (TCGA) and the Gene Ontology (GO) dataset. We identified two key differentially expressed redox genes (CYBA and SMPD3) by univariate Cox regression and utilised them to calculate the risk score of all samples. Based on the median of risk scores, we composed low-and high-risk groups and performed correlation analysis with immune cell infiltration and immune checkpoints. Finally, we constructed a nomogram of the prognostic model based on clinical factors and the risk score. We verified the predictive performance using receiver operating characteristic (ROC) and calibration curves. CYBA and SMPD3 were significantly related to the prognosis of patients with EC and used to construct a risk model. There were significant differences in survival, immune cell infiltration and immune checkpoints between the low-and high-risk groups. The nomogram developed with clinical indicators and the risk scores was effective in predicting the prognosis of patients with EC. In this study, a prognostic model constructed based on two redox-related genes (CYBA and SMPD3) were proved to be independent prognostic factors of EC and associated with tumour immune microenvironment. The redox signature genes have the potential to predict the prognosis and the immunotherapy efficacy of patients with EC.

The contributions and mechanisms of iron-microbes-biochar in constructed wetlands for nitrate removal from low carbon/nitrogen ratio wastewater.

The removal efficiency of nitrate from low carbon/nitrogen ratio wastewater has been restricted by the lack of organics for several decades. Here, a system coupling chemical reduction, microbial denitrification and constructed wetlands (RDCWs) was developed to investigate the effect and possible mechanisms for nitrate degradation. The results showed that this coupling system could achieve a nitrate removal efficiency of 97.07 ± 1.76%, 85.91 ± 3.02% and 56.63 ± 2.88% at a hydraulic retention time of 24 h, 12 h and 6 h with feeding nitrate of 15 mg L-1, respectively. These removal efficiencies of nitrate were partly caused by microbes and biochar with a contribution rate of 31.08 ± 4.43% and 9.50 ± 3.30%. Besides, microbes were closely related to iron and biochar for the removal of nitrate. Simplicispira was able to utilize hydrogen produced by iron corrosion as an electron donor while nitrate accepted electrons to be reduced. Porous biochar could release dissolved organic matter, which provided a good living circumstance and carbon source for microbes. Therefore, the RDCW system is potential for large-scale application due to its low cost and simple operation.

Bacteria-supported iron scraps for the removal of nitrate from low carbon-to-nitrogen ratio wastewater.

A novel bacteria-supported iron scraps (BSIS) system was developed for nitrate removal from low carbon-to-nitrogen ratio (C/N) wastewater. The system consisted of low-cost iron scraps and the accumulated denitrifying-related bacteria enriched from an Fe-wastewater environment when the system was operating. After operating for 39 d, the nitrate removal rate of the system increased to 73.55% within 24 h. The extraction of bacteria from the system revealed that iron scraps and bacteria had a synergistic effect on nitrate removal and bacteria only took effect when cooperating with iron. Microbial analysis using high-throughput sequencing showed that Hydrogenophaga, which is closely related to hydrogenotrophic denitrification, became the dominant genus in the system. The system provides a promising approach to the treatment of nitrate in low C/N wastewater and it has the potential for large-scale application due to the low cost, simple operation and relatively high removal rate.