Promoting nitrogen conversion in aerobic biotransformation of swine slurry with the co-application of manganese sulfate and biochar.

This study aimed to explore the co-application of MnSO4 (Mn) and biochar (BC) in nitrogen conversion during the composting process. A 70-day aerobic composting was conducted using swine slurry, supplemented with different levels of Mn (0, 0.25%, and 0.5%) and 5% BC. The results demonstrated that the treatment with 0.5MnBC had the highest levels of NH4+-N (3.07 g kg-1), TKN (29.90 g kg-1), and NO3--N (1.94 g kg-1) among all treatments. Additionally, the 0.5MnBC treatment demonstrated higher urease, protease, nitrate reductase, and nitrite reductase activities than the other treatments, with the peak values of 18.12, 6.96, 3.57, and 15.14 mg g-1 d-1, respectively. The addition of Mn2+ increased the total organic nitrogen content by 29.59%-47.82%, the acid hydrolyzed ammonia nitrogen (AN) content by 13.84%-57.86% and the amino acid nitrogen (AAN) content by 55.38%-77.83%. The richness of Chloroflexi and Ascomycota was also enhanced by the simultaneous application of BC and Mn. Structural equation modeling analysis showed that Mn2+ can promote the conversion of Hydrolyzed Unknown Nitrogen (HUN) into AAN, and there is a positive association between urease and NH4+-N according to redundancy analysis. Firmicutes, Basidiomycota, and Mortierellomycota showed significant positive correlations with ASN, AN, and NH4+-N, indicating their crucial roles in nitrogen conversion. This study sheds light on promoting nitrogen conversion in swine slurry composting through the co-application of biochar and manganese sulfate.

Exploring carbon conversion and balance with magnetite-amended during pig manure composting.

This study was designed to explore the magnetite in maturation and humification during pig manure (PM) and wolfberry branch fillings (BF) composting. Different proportions of magnetite (T1, 0%; T2, 2.5%; T3, 5%; T4, 7.5%;) were blended with PM for 50 days of composting. The findings indicated magnetite amendment has no influence on the maturity, and the 5% ratio significantly promoted humic acid (HA) formation and fulvic acid (FA) decomposition compared to other treatments. Compared to T1, magnetite addition significantly increased CO2 and CH4 emissions by 106.39%-191.69% and 6.88-13.72 times. The further analysis suggested that magnetite improved Ruminofilibacter activity were significantly positively associated with HA, and C emissions. The further PICRUSt 2 analysis showed membrane transport may enhance environmental information processing by magnetite. Overall, these results demonstrated higher organic matter (OM) degradation and HA formation with an additional increase in microbial activity highlighted advantages of using magnetite during PM composting.

Sulfur-aided aerobic biostabilization of swine manure and sawdust mixture: Humification and carbon loss.

To investigate how sulfur addition affects humification and carbon loss during swine manure (SM) biostabilisation, various proportions of sulfur, i.e., 0 (CK), 0.2%-0.8% (S1-S4) were added to SM in a 70-day pilot-scale test. Compared to CK (16.07%), sulfur addition resulted in the mineralization of 17.05%-24.27% of the total organic carbon. Sulfur addition also reduced CH4 emissions, which were 3.7%-29.3% lower than that of CK. The total global warming potential values were in the range of 913.1-968.2 g CO2 eq kg-1 for all treatments. Although the sulfur-added treatments showed lower HA/FA ratios than CK after 70 days, no significant impact on the maturity of the final products was observed. Sulfur addition impacted the microbial community, CH4, CO2, N2O emissions, and affected the variation of temperature in biowaste biostabilization. These discoveries provided an important basis for understanding the function of sulfur in regulating the aerobic bio-decomposition of organic waste.

Powerful and robust inference of complex phenotypes' causal genes with dependent expression quantitative loci by a median-based Mendelian randomization.

Isolating the causal genes from numerous genetic association signals in genome-wide association studies (GWASs) of complex phenotypes remains an open and challenging question. In the present study, we proposed a statistical approach, the effective-median-based Mendelian randomization (MR) framework, for inferring the causal genes of complex phenotypes with the GWAS summary statistics (named EMIC). The effective-median method solved the high false-positive issue in the existing MR methods due to either correlation among instrumental variables or noises in approximated linkage disequilibrium (LD). EMIC can further perform a pleiotropy fine-mapping analysis to remove possible false-positive estimates. With the usage of multiple cis-expression quantitative trait loci (eQTLs), EMIC was also more powerful than the alternative methods for the causal gene inference in the simulated datasets. Furthermore, EMIC rediscovered many known causal genes of complex phenotypes (schizophrenia, bipolar disorder, and total cholesterol) and reported many new and promising candidate causal genes. In sum, this study provided an efficient solution to discriminate the candidate causal genes from vast amounts of GWAS signals with eQTLs. EMIC has been implemented in our integrative software platform KGGSEE.