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Objective To explore the potential biomarkers for the diagnosis of primary brain stem injury （PBSI） by using metabonomics method to observe the changes of metabolites in rats with PBSI caused death. Methods PBSI, non-brain stem brain injury and decapitation rat models were established, and metabolic maps of brain stem were obtained by LC-MS metabonomics method and annotated to the HMDB database. Partial least square-discriminant analysis （PLS-DA） and random forest methods were used to screen potential biomarkers associated with PBSI diagnosis. Results Eighty-six potential metabolic markers associated with PBSI were screened by PLS-DA. They were modeled and predicted by random forest algorithm with an accuracy rate of 83.3%. The 818 metabolic markers annotated to HMDB database were used for random forest modeling and prediction, and the accuracy rate was 88.9%. According to the importance in the identification of cause of death, the most important metabolic markers that were significantly up-regulated in PBSI group were HMDB0038126 （genipinic acid, GA）, HMDB0013272 （N-lauroylglycine）, HMDB0005199 [（R）-salsolinol] and HMDB0013645 （N,N-dimethylsphingosine）. Conclusion GA, N-lauroylglycine, （R）-salsolinol and N,N-dimethylsphingosine are expected to be important metabolite indicators in the diagnosis of PBSI caused death, thus providing clues for forensic medicine practice.

Multi-focus image fusion means fusing a completely clear image with a set of images of the same scene and under the same imaging conditions with different focus points. In order to get a clear image that contains all relevant objects in an area, the multi-focus image fusion algorithm is proposed based on wavelet transform. Firstly, the multi-focus images were decomposed by wavelet transform. Secondly, the wavelet coefficients of the approximant and detail sub-images are fused respectively based on the fusion rule. Finally, the fused image was obtained by using the inverse wavelet transform. Among them, for the low-frequency and high-frequency coefficients, we present a fusion rule based on the weighted ratios and the weighted gradient with the improved edge detection operator. The experimental results illustrate that the proposed algorithm is effective for retaining the detailed images.

Soil nitrogen (N) transformation is mainly controlled by microorganisms. Different plant species have specific effects on soil ammonia‐oxidizing archaea (AOA) and bacteria (AOB). Furthermore, plant secondary metabolites have dramatic influences on soil N transformation and soil ammonia‐oxidizers. However, no study has directly linked the changes in soil AOA and AOB communities to N transformation due to different plant species' leaf leachates, including comparing invasive versus native plants. We selected three invasive species, Wedelia trilobata, Ipomoea cairica and Mikania micrantha, and two native species, Wedelia chinensis and Merremia hederacea, and incubated soil with high and low concentrations of leaf leachates from the five species. Soil N transformation and ammonia oxidizer communities (based on quantitative PCR and 16S rRNA high‐throughput sequencing) were determined. Leaf leachates significantly affected soil N transformation and soil AOA and AOB abundance, and the effects were dependent on the plant species and leachate concentration. The leachate of W. chinensis increased soil net nitrification rates (NNR), whereas that of M. micrantha increased soil nitrate (NO3−) and NNR. The leachate of M. micrantha increased AOB amoA genes, whereas that of M. hederacea decreased AOA amoA genes. At the higher concentration, all leachates showed inhibitory effects on the relative abundance of all AOA taxonomic groups. Phenolics, flavonoids and organic carbon in leaf leachates had a negative correlation with soil NO3−, NNR and the amoA genes of AOA and AOB, whereas NH4+ and NO3− in leachates showed a positive correlation. Among the five species, the invasive species M. micrantha had the strongest positive effect on soil N transformation and AOB abundance. The altered soil ammonia oxidizer communities and modified N process rates induced by leaf leachates provide an explanatory mechanism for the differential effects of plant species on N cycling. Highlights: Link changes in soil AOA and AOB to N cycling due to leaf leachates.Specific plants can dramatically alter soil ammonia‐oxidizer presence and abundance.Effects of invasive plants on soil N and AOB are mainly driven by M. micrantha.High concentrations of plant leachates reduced the relative abundance of AOA groups. [ABSTRACT FROM AUTHOR]