Biochar has proven to be a feasible additive for mitigating nitrogen loss during the composting process. This study aims to evaluate the influence of biochar addition on bacterial community and physicochemical properties changes, including ammonium (NH4+), nitrite (NO2-) and nitrate (NO3-) contents during the composting of poultry manure. The composting was carried out by adding 20% (w/w) of biochar into the mixture of poultry manure and rice straw with a ratio of 2:1, and the same treatment without biochar was prepared as a control. The finished product of control compost recorded the high contents of NO2- and NO3- (366 mg/kg and 600 mg/kg) with reduced the total NH4+ content to 10 mg/kg. Meanwhile, biochar compost recorded a higher amount of total NH4+ content (110 mg/kg) with low NO2- and NO3- (161 mg/kg and 137 mg/kg) content in the final composting material. The principal component analysis showed that the dynamics of dominant genera related to Halomonas, Pusillimonas, and Pseudofulvimonas, all of which were known as nitrifying and denitrifying bacteria, was significantly correlated with the dynamic of NO2- and NO3- content throughout the composting process. The genera related to Pusillimonas, and Pseudofulvimonas appeared as the dominant communities as the NO2- and NO3- increased. In contrast, as the NO2- and NO3- concentration decreased, the Halomonas genus were notably enriched in biochar compost. This study revealed the bacterial community shifts corresponded with the change of physicochemical properties, which provides essential information for a better understanding of monitoring and improving the composting process.
Traumatic brain injury (TBI) is a leading cause of death and disability in individuals worldwide. Producing a clinically relevant TBI model in small-sized animals remains fairly challenging. For good screening of potential therapeutics, which are effective in the treatment of TBI, animal models of TBI should be established and standardized. In this study, we established mouse models of closed head injury using the Shohami weight-drop method with some modifications concerning cognitive deficiency assessment and provided a detailed description of the severe TBI animal model. We found that 250 g falling weight from 2 cm height produced severe closed head injury in C57BL/6 male mice. Cognitive disorders in mice with severe closed head injury could be detected using passive avoidance test on day 7 after injury. Findings from this study indicate that weight-drop injury animal models are suitable for further screening of brain neuroprotectants and potentially are similar to those seen in human TBI.