Comprehensive Analysis Identifies and Validates the Tumor Microenvironment Subtypes to Predict Anti-Tumor Therapy Efficacy in Hepatocellular Carcinoma

ObjectiveThe objective of this study was to explore and verify the subtypes in hepatocellular carcinoma based on the immune (lymphocyte and myeloid cells), stem, and stromal cells in the tumor microenvironment and analyze the biological characteristics and potential relevance of each cluster.MethodsWe used the xCell algorithm to calculate cell scores and got subtypes by k-means clustering. In the external validation sets, we verified the conclusion stability by a neural network model. Simultaneously, we speculated the inner connection between clusters by pseudotime trajectory analysis and confirmed it by pathway enrichment, TMB, CNV, etc., analysis.ResultAccording to the results of the consensus cluster, we chose k = 4 as the optimal value and got four different subtypes (C1, C2, C3, and C4) with different biological characteristics based on infiltrating levels of 48 cells in TME. In univariable Cox regression, the hazard ratio (HR) value of C3 versus C1 was 2.881 (95% CI: 1.572–5.279); in multivariable Cox regression, we corrected the age and TNM stage, and the HR value of C3 versus C1 was 2.510 (95% CI: 1.339–4.706). C1 and C2 belonged to the immune-active type, C3 and C4 related to the immune-insensitive type and the potential conversion relationships between clusters. We established a neural network model, and the area under the curves of the neural network model was 0.949 in the testing cohort; the same survival results were also observed in the external validation set. We compared the differences in cell infiltration, immune function, pathway enrichment, TMB, and CNV of four clusters and speculated that C1 and C2 were more likely to benefit from immunotherapy and C3 may benefit from FGF inhibitors.DiscussionOur analysis provides a new approach for the identification of four tumor microenvironment clusters in patients with liver cancer and identifies the biological differences and predicts the immunotherapy efficacy between the four subtypes

Chemical composition and antioxidant activity of petroleum ether fraction of Rosmarinus officinalis

The presented study examines the chemical composition and antioxidant activity of the petroleum ether fraction of Rosmarinus officinalis (PEF-RO), which was obtained via 75 % ethanol extraction followed by petroleum ether extraction. The obtained fractions were analyzed by gas chromatography-mass spectrometry (GC-MS). The in vitro antioxidant activity of PEF-RO was investigated using various assays, including 1,1-diphenyl-2-picrylhydrazyl (DPPH), 2,2′-azinobis-(3-ethylbenzthiazoline-6-sulfonate (ABTS) free radical scavenging, and ferric reducing antioxidant power (FRAP) method. A total of 82 chemical components were successfully identified, totaling 10.06 % of PEF-RO content. The identified components consisted of 24 hydrocarbons, 14 ketones, 16 alcohols, 4 phenols, 14 esters, and 10 other compounds. Notably, verbenone (2.4377 %), vitamin A (0.6854 %), trans-geraniol (0.5998 %), linolenic acid (0.5713 %), and 1,8-eucalyptol (0.5323 %) were the most abundant compounds, and there are many trace components in PEF-RO. PEF-RO's IC50 values of DPPH and ABTS free radical scavenging were determined as 0.36 mg/mL and 0.19 mg/mL, respectively. FRAP-method was employed to measure the total antioxidant energy of PEF-RO, which displayed good antioxidant activity. The obtained data provides the foundation for the comprehensive development and utilization of Rosmarinus officinalis

Silicon fertilization enhances the resistance of tobacco plants to combined Cd and Pb contamination : Physiological and microbial mechanisms

Remediation of soil contaminated with cadmium (Cd) and lead (Pb) is critical for tobacco production. Silicon (Si) fertilizer can relieve heavy metal stress and promote plant growth, however, it remains unknown whether fertilization with Si can mitigate the effects of Cd and Pb on tobacco growth and alter microbial community composition in polluted soils. Here we assessed the effect of two organic (OSiFA, OSiFB) and one mineral Si fertilizer (MSiF) on Cd and Pb accumulation in tobacco plants, together with responses in plant biomass, physiological parameters and soil bacterial communities in pot experiments. Results showed that Si fertilizer relieved Cd and Pb stress on tobacco, thereby promoting plant growth: Si fertilizer reduced available Cd and Pb in the soil by 37.3 % and 28.6 %, respectively, and decreased Cd and Pb contents in the plant tissue by 42.0–55.5 % and 17.2–25.6 %, resulting in increased plant biomass by 13.0–30.5 %. Fertilization with Si alleviated oxidative damage by decreasing malondialdehyde content and increasing peroxidase and ascorbate peroxidase content. In addition, Si fertilization increased photosynthesis, chlorophyll and carotenoid content. Microbial community structure was also affected by Si fertilization. Proteobacteria and Actinobacteria were the dominant phylum in the Cd and Pb contaminated soils, but Si fertilization reduced the abundance of Actinobacteria. Si fertilization also altered microbial metabolic pathways associated with heavy metal resistance. Together, our results suggest that both organic and mineral Si fertilizers can promote tobacco growth by relieving plant physiological stress and favoring a heavy metal tolerant soil microbial community

Inversion of Space Debris Material by Synthetic Light Curves

Ground-based optical observation of GEO space debris plays an essential role in tracking, identifying, cataloging, and classifying space debris. The factors that affect the brightness of space debris include size, surface material, illumination geometry, attitude, shape, position, and so on. In order to better understand the influence of the above factors on the brightness of space debris, the synthetic light curves are analyzed. The Ashikhmin–Shirley model is chosen to simulate the light curves of space debris. The effects of orbit, attitude, model parameters, and the location of the observation station on the synthetic light curves are analyzed by the control variable method. Based on the Markov Chain Monte Carlo method (MCMC), the optimal model parameters that characterize the surface material of space debris can be obtained by comparing the synthetic light curves with the observed light curves under certain shape, orbit, and attitude characteristics. The results are roughly in good agreement with those measured in the laboratory

Multi-household grazing management pattern maintains better soil fertility

In addition to changes in land use and cover, changes in land management pattern can also have a significant effect on soil fertility. However, to date, changes in grassland grazing management pattern caused by policies have received less attention in terms of their impact on soil fertility. In this paper, we investigated the influence of two different grazing management patterns: the multi-household grazing management pattern (consisting of pastures managed by two or more households with no fences separating them) and the single-household grazing pattern (with fences between adjacent pastures managed by different households), which were implemented after the enactment of grassland contract policy, on soil fertility in the Qinghai-Tibetan Plateau. Our hypothesis was that soil fertility differed between the two grazing management patterns. We selected five study sites with both grazing management patterns in Maqu County on the eastern Qinghai-Tibetan Plateau and sampled 30 winter grasslands from each grazing management pattern to explore differences in soil organic carbon, soil total nitrogen, and soil total phosphorus. We showed that these indicators of fertility status were significantly greater under the multi-household grazing management pattern (47 g C kg−1, 4.6 g N kg−1, and 0.77 g P kg−1) compared to the single-household grazing management pattern (43 g C kg−1, 4.3 g N kg−1, and 0.73 g P kg−1). This is the first study of the effects of grazing management pattern on soil fertility in this environment, and it indicated that the multi-household grazing management pattern could maintain better soil fertility and help to support sustainable use of these grasslands