Background: Manure and biochar soil amendments have shown many benefits to soil quality and crop productivity. This study aimed to reveal the effects of biochar and manure applications on soil fertility improvement and crop productivity in yellow cinnamon soil.Results: This study based on a 5-year field experiment. Four treatments were designed, included the control (CK), biochar amendment, manure amendment, and both biochar and manure amendment (BM). The results showed that: after five years, both biochar and manure treatment improved soil structure by increasing soil mean weight diameter (MWD), and soil water and nutrient supply was also increased by increasing the contents of water content, available potassium and available phosphorus. The productivity was also enhanced as wheat yield under the biochar, manure, and BM treatments increased by 3.59–11.32% compared with CK. In addition, biochar and manure treatment increased soil microbial biomass carbon (MBC) by > 15%, and soil total nematode abundance was significantly increased. Furthermore, the nematode community structure was significantly affected by biochar and manure treatment, dominant trophic group in CK was herbivores, but bacterivores were dominant in the biochar and manure treatments. The distribution of nematode genera was closely related to soil chemical properties and microbial biomass. Increases in the Shannon's diversity index, and decreases in the dominance index and summed maturity index after the 5-year treatment indicated a sustainable soil ecosystem after the biochar and manure applications.Conclusions: These findings indicate that biochar and manure result in better soil quality and increased productivity in yellow cinnamon soil.

Objective. To improve the diagnostic capacity of serum biomarkers for colorectal cancer (CRC), we introduced three novel indicators, namely, the C-X-C motif chemokine ligand 5 (CXCL5), stanniocalcin 2 (STC2), and chitinase 3 like 1 (CHI3L1) and assessed their performances in the detection of CRC. Methods. A total of 887 serum samples (153 health, 342 polyps, and 392 CRCs) were collected. Concentrations of CXCL5, STC2, and CHI3L1 were measured by the ELISA. CEA and CA199 were determined by electrochemiluminescence. Binary logistic regression was used to build the combination model. ROC analysis was used to evaluate the performance of biomarkers alone or in combination. Results. Model_2 that based on CXCL5, STC2, and CHI3L1 was the best approach in discriminating CRC from non-CRC controls (AUC, 0.943 (0.9220.960); sensitivity, 0.848; specificity, 0.917; and accuracy, 0.887 in the training cohort and 0.959 (95 CI 0.9270.980), 0.878, 0.917, and 0.900 in the testing cohort, respectively). In the detection of early CRC, Model_2 revealed AUC, sensitivity, specificity, and accuracy of 0.925 (0.8970.947), 0.793, 0.917, and 0.886 in the training cohort and those of 0.926 (0.9790.959), 0.786, 0.931, and 0.898 in the testing cohort. Furthermore, Model_2 exhibited an excellent diagnostic performance in CEA-negative cases (0.938 (0.9130.957), 0.826, 0.917, and 0.888 in the training cohort and 0.961 (0.9250.983), 0.887, 0.931, and 0.918 in the testing cohort). As used alone, STC2 achieved the capacities that is second only to that of Model_2 (0.866 (0.8370.892), 0.859, 0.842, and 0.853 in the training cohort and 0.887 (0.8420.923), 0.922, 0.799, and 0.853 in the testing cohort). STC2 alone also yielded acceptable results for early CRC detection (0.815 (0.7760.849), 0.767, 0.849, and 0.829 in the training cohort and 0.870 (0.8120.914), 0.952, 0.799, and 0.833 in the testing cohort). Moreover, STC2 maintained diagnostic accuracy for CRC patients with negative CEA (0.874 (0.8420.901), 0.862, 0.849, and 0.853 in the training cohort and 0.898 (0.8480.936), 0.930, 0.801, and 0.842 in the testing cohort). In comparison, the performances of the CEA and CA199 based Model_1 were far from satisfactory, especially in early cases (0.767 (0.7260.805), 0.491, 0.863, and 0.771 in the training cohort and 0.817 (0.7540.870), 0.476, 0.889, and 0.796 in the testing cohort). Conclusions. STC2 was a promising serum biomarker for CRC diagnosis either used alone or in combination with CXCL5 and CHI3L1.

In a greenhouse experiment, we examined the behavior of biochar in arable soil to demonstrate that these supplements can boost soil carbon storage, as well as to track changes in microbial biomass and identify the microbial communities that use these biochars. In order to ascertain if biochar can consistently alter soil microbial activities, we studied the impact of biochar combination treatments on 16S rRNA gene diversity. In soil treated with biochar, there was a rise in the relative abundance of taxa belonging to the phyla Actinobacteria and Gemmatimonadetes, despite the overall diversity decreasing with biochar addition. According to all of these observations, pyrogenic carbon has a major effect on the composition of the soil microbial community and enriches keystone taxa within the parent soil microbial community. Certain species experienced increases throughout the biochar-amended incubation period, despite the total diversity declining following biochar amendments. The phyla Actinobacteria and Gemmatimonadetes increased in the relative abundance of bacteria in soil treated with biochar, according to DNA sequencing of these species. In summary, these findings show that biochar significantly impacts the constitution and composition of the soil microbial community and enriches important taxa within the parent soil microbial community.

Background: Studies have shown that some viral infections cause structural changes in the intestinal microflora, but little is known about the effects of tumorigenic viral infection on the intestinal microflora of chickens. Results: A 29-week commercial layer flock positive for avian leukosis virus-J (ALV-J), Marek’s disease virus (MDV) and avian reticuloendotheliosis virus (REV) was selected, and fresh fecal samples were collected and examined for the composition of the gut microflora by Illumina sequencing of the V3-V4 region of the 16S rRNA gene. The operational taxonomic units (OTUs) of the fecal microbiota differentiated the chickens infected with only ALV-J and those coinfected with ALV-J and MDV or REV from infection-negative chickens. The enrichment and diversity of cloacal microflora in chickens infected with ALV-J alone were slightly different from those in the infection-negative chickens. However, the diversity of cloacal microflora was significantly increased in chickens coinfected with both ALV-J and MDV or REV. Conclusions: The intestinal microbiota was more strongly disturbed in chickens after coinfection with ALV-J and MDV or REV than after infection with ALV-J alone, and there may be underlying mechanisms by which the capacity for the stabilization of the intestinal flora was impaired due to viral infection and tumorigenesis.