Proteomic and metabolomic features in patients with HCC responding to lenvatinib and anti-PD1 therapy.

Combination therapy (lenvatinib/programmed death-1 inhibitor) is effective for treating unresectable hepatocellular carcinoma (uHCC). We reveal that responders have better overall and progression-free survival, as well as high tumor mutation burden and special somatic variants. We analyze the proteome and metabolome of 82 plasma samples from patients with hepatocellular carcinoma (HCC; n = 51) and normal controls (n = 15), revealing that individual differences outweigh treatment differences. Responders exhibit enhanced activity in the alternative/lectin complement pathway and higher levels of lysophosphatidylcholines (LysoPCs), predicting a favorable prognosis. Non-responders are enriched for immunoglobulins, predicting worse outcomes. Compared to normal controls, HCC plasma proteins show acute inflammatory response and platelet activation, while LysoPCs decrease. Combination therapy increases LysoPCs/phosphocholines in responders. Logistic regression/random forest models using metabolomic features achieve good performance in the prediction of responders. Proteomic analysis of cancer tissues unveils molecular features that are associated with side effects in responders receiving combination therapy. In conclusion, our analysis identifies plasma features associated with uHCC responders to combination therapy.

The Intratumoral Bacterial Metataxonomic Signature of Hepatocellular Carcinoma.

Microbiota is implicated in hepatocellular carcinoma (HCC). The spectrum of intratumoral microbiota associated with HCC progression remains elusive. Fluorescence in situ hybridization revealed that microbial DNAs were distributed in the cytosol of liver hepatocytes and erythrocytes. Viable anaerobic or aerobic bacteria were recovered in HCC tissues by fresh tissue culture. We performed a comprehensive DNA sequencing of bacterial 16S rRNA genes in 156 samples from 28 normal liver, 64 peritumoral, and 64 HCC tissues, and the DNA sequencing yielded 4.2 million high-quality reads. Both alpha and beta diversity in peritumor and HCC microbiota were increased compared to normal controls. The most predominant phyla in HCC were Patescibacteria, Proteobacteria, Bacteroidota, Firmicutes, and Actinobacteriota. phyla of Proteobacteria, Firmicutes, and Actinobacteriota, and classes of Bacilli and Actinobacteria, were consistently enriched in peritumor and HCC tissues, while Gammaproteobacteria was especially abundant in HCC tissues compared to normal controls. Streptococcaceae and Lactococcus were the marker taxa of HCC cirrhosis. The Staphylococcus branch and Caulobacter branch were selectively enriched in HBV-negative HCCs. The abundance of Proteobacteria, Gammaproteobacteria, Firmicutes, Actinobacteriota, and Saccharimonadia were associated with the clinicopathological features of HCC patients. The inferred functions of different taxa were changed between the microbiota of normal liver and peritumor/HCC. Random forest machine learning achieved great discriminative performance in HCC prediction (area under the curve [AUC] = 1.00 in the training cohort, AUC = 0.950 for top five class signature, and AUC = 0.943 for the top 50 operational taxonomy units [OTUs] in the validation cohort). Our analysis highlights the complexity and diversity of the liver and HCC microbiota and established a specific intratumoral microbial signature for the potential prediction of HCC. IMPORTANCE Gut microbiome is an important regulator of hepatic inflammation, detoxification, and immunity, and contributes to the carcinogenesis of liver cancer. Intratumoral bacteria are supposed to be closer to the tumor cells, forming a microenvironment that may be relevant to the pathological process of hepatocellular carcinoma (HCC). However, the presence of viable intratumoral bacteria remains unclear. It is worth exploring whether the metataxonomic characteristics of intratumoral bacteria can be used as a potential marker for HCC prediction. Here, we present the first evidence of the existence of viable intratumoral bacteria in HCC using the tissue culture method. We revealed that microbial DNAs were distributed in the cytosol of liver hepatocytes and erythrocytes. We analyzed the diversity, structure, and abundance of normal liver and HCC microbiota. We built a machine learning model for HCC prediction using intratumoral bacterial features. We show that specific taxa represent potential targets for both therapeutic and diagnostic interventions.

Dual role of O2 concentration on the reducing gases produced and NO reduction during sewage sludge combustion in pilot scale cement precalciner.

The reducing gases produced and NO reduction by sewage sludge combustion were investigated in a self-made cement precalciner. The dual role of O2 concentration (0-5 vol%) in the production characteristics of reducing gases and the reduction efficiency of NO were evaluated experimentally. TG-FTIR analysis demonstrated that the key reducing gaseous species produced by sewage sludge combustion were HCN, NH3, CO, and CH4. And experiments demonstrated that O2 concentration had pronounced effects on NH3 distribution, the maximum production rate was obtained at an O2 concentration of 3 vol%. Meanwhile, the reducing gases NH3 and CO were the key species for NO reduction in the cement precalciner, and the reduction efficiency of NO, when reduced by NH3, increased with an increase in O2 concentration, while the reduction performance of NO by CO was limited by O2 concentration. Therefore, O2 concentration greatly influences NO reduction efficiency by sewage sludge combustion; the maximum NO reduction efficiency was 61.67% at an O2 concentration of 3 vol%. The difference in NO reduction by sewage sludge combustion under different O2 concentrations was primarily attributed to NH3 production rate and NO reduction by NH3 and CO, which is greatly affected by O2 concentration. Sewage sludge combustion can result in NO reduction in the cement kiln flue gas and resource utilisation of sewage sludge.

Simultaneous Removal of SO2 and NO by O3 Oxidation Combined with Wet Absorption.

The effects of ozone concentration, NaOH concentration, type and concentration of additives, initial pH, temperature, and NO and SO2 concentration on simultaneous removal of NO and SO2 were studied through ozone oxidation combined with wet absorption. Results indicated that ozone concentration and the type and concentration of additives had the most significant effect on NO removal. The optimal ozone concentration was 250 ppm (NO/NO2 = 1), and the best additive was KMnO4. The removal efficiency of NO x was as high as 97.86% when NO/NO2 = 1, and the concentration of KMnO4 was 0.025 mol/L. Considering economic and other factors, the KMnO4 concentration was selected to be 0.006 mol/L. At this time, the removal efficiencies of NO x and SO2 were 81.35 and 100%, respectively. This method has potential application prospects for simultaneous removal of SO2 and NO in the industrial flue gas.

Correction: Mechanistic study on NO reduction by sludge reburning in a pilot scale cement precalciner with different CO2 concentrations.

[This corrects the article DOI: 10.1039/C9RA04065J.].

Mechanistic study on NO reduction by sludge reburning in a pilot scale cement precalciner with different CO2 concentrations.

An experimental study on the effects of CO2 concentration on the release of reducing gases and the NO reduction efficiency by sludge reburning was carried out in a pilot scale cement precalciner. The results indicate that sludge reburning shows an ideal NO reduction activity. The best NO reduction efficiency of 54% is reached when the CO2 concentration is 25 vol%. Characteristic analysis of the sludge shows that the main types of reducing gases generated by sludge reburning are HCN, NH3, CO and CH4. Among them, CO2 concentration plays a crucial role in the release of HCN, CO and CH4. The mechanistic study indicates that NO reduction is dominated by homogeneous reduction during the sludge reburning process, in particular the reducing gases of CO and NH3 have significant influences on the NO reduction. Meanwhile, the effect of CO2 concentration on NO reduction is mainly due to the difference in CO release. The results of the present study not only provide insight into the mechanism of NO reduction by sludge reburning, but could also contribute to the development of NO X removal technology in the cement industry.