The biological nitrogen removal technology utilizing heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria has shown effectiveness in wastewater treatment. However, the nitrogen removal efficiency of HN-AD bacteria significantly decreases as the salinity increases. To tackle the challenge of treating high-salt and high-nitrogen wastewater, we isolated a moderately halophilic HN-AD strain 5505 from a salt lake in Xinjiang. The strain was identified based on morphological, physiological, and biochemical characteristics and the 16S rRNA gene sequence. Single-factor experiments were carried out with NH₄⁺-N, NO₃^--N, and NO₂^--N as sole or mixed nitrogen sources to study the nitrifying effect, denitrifying effect, and nitrogen metabolism pathway of the strain. The strain was identified as Halomonas sp.. It can grow in the presence of 1%-25% (W/V) NaCl and exhibited efficient nitrogen removal ability in the presence of 3%-8% NaCl. At the optimal NaCl concentration (8%), the strain showed the NH₄⁺-N, NO₃^--N and NO₂^--N removal rates of 100.0%, 94.11% and 74.43%, respectively. Strain 5505 removed inorganic nitrogen mainly by assimilation, which accounted for over 62.68% of total nitrogen removal. In the presence of mixed nitrogen sources, strain 5505 showed a preference for utilizing ammonia, with a potential HN-AD pathway of NH₄⁺→NH₂OH→NO₂^-→NO₃^-→NO₂^-→NO/N₂O/N₂. The findings provide efficient salt-tolerant bacterial resources, enhance our understanding of biological nitrogen removal, and contribute to the nitrogen removal efficiency improvement in the treatment of high-salt and high-nitrogen wastewater.
Halomonas/classification* ; Nitrogen/isolation & purification* ; Denitrification ; Nitrification ; Wastewater/microbiology* ; Aerobiosis ; Biodegradation, Environmental ; Salinity

With the widespread application of information technology in the field of Traditional Chinese Medicine(TCM),the data in the TCM domain is becoming increasingly rich.The emergence of data-driven research in TCM has utilized knowledge graphs for the management,analysis,and presentation of TCM data,becoming a crucial method for the inheritance and innovation of Traditional Chinese Medicine.Therefore,reasoning based on TCM knowledge graphs has become a hot topic in contemporary TCM research.In order to better utilize knowledge graph reasoning technology to promote innovation and development in TCM,this article,after providing an overview of TCM knowledge graph reasoning,focuses on the development of knowledge graph reasoning in TCM and its applications from three perspectives:logic rule-based,distributed representation,and neural network-based methods.Finally,the article summarizes the advantages and disadvantages of knowledge reasoning methods and provides prospects for research and applications in TCM knowledge graph reasoning,including studies on interpretability,temporal knowledge graphs,and the fusion of multimodal information.

With the widespread application of information technology in the field of Traditional Chinese Medicine(TCM),the data in the TCM domain is becoming increasingly rich.The emergence of data-driven research in TCM has utilized knowledge graphs for the management,analysis,and presentation of TCM data,becoming a crucial method for the inheritance and innovation of Traditional Chinese Medicine.Therefore,reasoning based on TCM knowledge graphs has become a hot topic in contemporary TCM research.In order to better utilize knowledge graph reasoning technology to promote innovation and development in TCM,this article,after providing an overview of TCM knowledge graph reasoning,focuses on the development of knowledge graph reasoning in TCM and its applications from three perspectives:logic rule-based,distributed representation,and neural network-based methods.Finally,the article summarizes the advantages and disadvantages of knowledge reasoning methods and provides prospects for research and applications in TCM knowledge graph reasoning,including studies on interpretability,temporal knowledge graphs,and the fusion of multimodal information.