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Summary: 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.

ABSTRACT 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.

The feasibility of removal of sulfate ions from the sodium alkali FGD wastewater using the ettringite precipitation method was evaluated. Factors affecting the removal of sulfate ions, such as NaAlO2 dosage, Ca(OH)2 dosage, solution temperature, anions (Cl−, NO3− and F−), and heavy metal ions (Mg2+ and Mn2+), were investigated, and the optimal experimental conditions for the removal of sulfate ions were determined. Experimental results indicate that the ettringite precipitation method can effectively remove SO42− with removal efficiency of more than 98%. All the investigated factors have influences on the removal of sulfate ions, and among them, the dosage of reagents, solution temperature, and fluoride ions have the strongest influence. In addition, the method can effectively synergistically remove F− and heavy metal ions with removal efficiencies of more than 90% and 99%, respectively; meanwhile, Cl− and NO3− also can be removed minimally by the method. The result of actual wastewater treatment shows that the method is feasible for treating high-concentration sulfate wastewater. The ettringite precipitation method has the potential to be a commercial application in the future.

The desulfurization and denitrification wastewater (DDW) from the wet flue gas treatment project is difficult to be treated and recycled because of high chloride ion (Cl−) concentration. Cl− can cause equipment and piping corrosion. However, there is a lack of cost-effective treatment technologies for the removal of Cl− from the DDW. In this research, the feasibility of Cl− removal from the DDW using Friedel’s salt precipitation method was evaluated. Factors affecting the Cl− removal, such as Ca(OH)2 dosage, NaAlO2 dosage, solution’s initial pH, solution’s temperature, reaction time, stirring speed, and anions (SO42−, NO3−, and F−), were investigated, and the optimal experimental conditions for Cl− removal were determined. Experimental results showed that Friedel’s salt precipitation method can remove Cl− effectively and can achieve synergistic removal of SO42−, F−, and heavy metal ions. Under the best experimental conditions, the average removal efficiencies of Cl−, SO42−, F−, and heavy metal ions reach more than 85%, 98%, 94%, and 99%, respectively. The Cl− removal mechanism studies showed that Cl− can be removed by precipitation as Ca4Al2Cl2(OH)12. The purified wastewater and the precipitated solid can be reused to reduce the consumption of water and alkali. Friedel’s salt precipitation method is an effective control technology for the synergistic removal of Cl−, SO42−, F−, and heavy metal ions and has enormous potential to be applied in the industrial wastewater treatment field.

A new paraffin/surfactant/water emulsion (PSW) for volatile organic compounds (VOCs) controlling was prepared and its potential for VOCs removal was investigated. Results indicated that PSW-5 (5%, v/v) provided higher toluene absorption efficiency (90.77%) than the other absorbents used. The saturation pressure, Henry’s constant, and activity coefficient of toluene in PSW-5 were significantly lower than those in water, and toluene solubility (1.331 g·L−1) in the PSW-5 was more than 2.5 times higher than the value in water. Several factors potentially affecting the toluene absorption efficiency were systematically investigated. The results suggested that concentration and pH of PSW, absorption temperature, and gas flow rate all had a strong influence on the toluene absorption, but the inlet concentration of toluene had little effect on the toluene absorption. There were different absorbing performances of PSW-5 on different VOCs, and the ketones, esters, and aromatics were more easily removed by the PSW-5 than the alkanes. Regeneration and reuse of the PSW were possible; after 3 runs of regeneration the absorption efficiency of PSW-5 for toluene also could reach 82.42%. So, the PSW is an economic, efficient, and safe absorbent and has a great prospect in organic waste gas treatment.

When high performance computing platforms are widely used for rendering application, scheduling of rendering jobs is crucial due to job starvation and resource fragmentation problems in the existing scheduling strategies. Meanwhile, these strategies rarely consider a tradeoff with fairness and performance. Moreover, the traditional task-centered assignment method and naïve load balancing strategy cannot make full use of rendering resources. Aiming at solving these issues, an efficient two-level hierarchy job scheduling and task dispatching strategy (RF-FD) for cluster rendering system is proposed. Specifically, the reservation-based FirstFit (RF) job scheduling strategy and feedback- based tasks distribution (FD) strategy are integrated to obtain the maximization of system performance and load balancing. The RF strategy uses the ideology of reservation on low-priority jobs to maximize the resources utilization rate when the jobs are blocked. And the FD strategy uses feedback of resource usage to choose an appropriate number of threads for the renderer and then divides rendering nodes into fine-granularity rendering units to balance load distribution. With different evaluation metrics, the experimental results demonstrate that the proposed strategy outperforms the existing scheduling strategies combining with the fixed threads and naïve load balancing method while guaranteeing the fairness. [ABSTRACT FROM AUTHOR]