In general, bioassay-guided fractionation and isolation of bioactive constituents from botanical materials frequently ended up with the reward of a single compound. However, botanical materials typically exert their therapeutic actions through multi-pathway effects due to the intrinsic complex nature of chemical constituents. In addition, the content of bioactive compounds in botanical materials is largely dependent on humidity, temperature, soil, especially geographical origins, from which rapid and accurate identification of plant materials is pressingly needed. These long-standing obstacles collectively impede the deep exploitation and application of these versatile natural sources. To address the challenges, a new paradigm integrating biogravimetric analyses and machine learning-driven origin classification (BAMLOC) was developed. The biogravimetric analyses are based on absolute qHNMR quantification and in vivo zebrafish model-assisted activity index calculation, by which bioactive substance groups jointly responsible for the bioactivities in all fractions are pinpointed before any isolation effort. To differentiate origin-different botanical materials varying in the content of bioactive substance groups, principal component analysis, linear discriminant analysis, and hierarchical cluster analysis in conjunction with supervised support vector machine are employed to classify and predict production areas based on the detection of volatile organic compounds by E-nose and GC-MS. Expanding BAMLOC to Codonopsis Radix enables the identification of polyacetylenes and pyrrolidine alkaloids as the bioactive substance group for immune restoration effect and accurately determines the origins of plants. This study advances the toolbox for the discovery of bioactive compounds from complex mixtures and lays a more definitive foundation for the in-depth utilization of botanical materials.

Objective To investigate the role and mechanism of suramin(Sur)in acetaminophen(APAP)-induced acute liver injury in mice.Methods 8-10 weeks old C57BL/6J mice were randomly divided into the APAP group and APAP+Sur group(20 mg/kg suramin was injected 1 h before).After 18 hrs of fasting,400 mg/kg APAP was injected intraperitoneally to establish a mouse model of acute liver failure and the survival rate was recorded.An acute liver injury model of mice was established via intraperitoneal injection of 300 mg/kg APAP(other conditions remained unchanged).A control group was also established,with liver tissues and serum collected at 0,2,and 12 hours post-APAP treatment.ELISA and CBA techniques were adopted to detect the release of alanine aminotransferase(ALT)and aspartate aminotransferase(AST)in serum and the secretion of inflammatory factors.H&E staining and immunohistochemistry were used to detect liver tissue necrosis and inflammatory cell infiltration.DCFA-DH and ELISA techniques were used to detect the levels of reactive oxygen species(ROS),malondialdehyde(MDA)and glutathione(GSH)in liver tissues.Western blotting was employed to assess the activation of the JNK signaling pathway in liver tissues.Results Suramin treatment improved the survival rate of APAP-induced mice,reduced the release of transaminases and inflammatory factors in serum,and alleviated APAP-induced liver cell necrosis and inflammatory cell infiltration in the liver.Suramin treatment delayed APAP-induced GSH depletion in the liver,reduced MDA and ROS levels,and inhibited JNK pathway activation.Conclusion This study has confirmed the protective effect of suramin against acetaminophen-induced acute liver injury in mice.The mechanism is potentially related to oxidative stress and inflammation.

Objective To explore the feasibility of blood oxygen level-dependent (BOLD) MRI to detect the chronic hepatitis b-induced early kidney injury. Methods Seventeen clinically diagnosed chronic hepatitis b patients with early kidney injury and 10 healthy volunteers were enrolled in this preliminary study. The 17 patients underwent dynamic nuclear renography and then subdivided into stage 1 kidney injury group (n=7) and stage 2 kidney injury group (n=10). All of the enrolled subjects underwent BOLD examination and T2* relaxation rates (R2*) of renal cortex and medulla of split kidney, and the ratio between them (R2*med/cor) were measured separately. One-way analysis of variance (ANOVA) were performed on the control group and chronic hepatitis b patients group (kidney injury stage 1 and stage 2 group) to compare the difference of renal cortical and medullary R2*values and R2*med/cor ratio. ROC curves were used to evaluate the efficacy of renal cortical and medullary R2* values and R2*med/cor ratio to diagnose the chronic hepatitis b-induced kidney injury. Results The cortical R2*values of control group, stage 1 kidney injury group and stage 2 kidney injury group were(16.87 ± 0.74)/s,(17.88 ± 0.73)/s,(20.29 ± 2.87)/s, respectively;the medullar R2*values of control group, stage 1 kidney injury group and stage 2 kidney injury group were (28.07±1.03)/s,(31.14±2.49)/s,(32.81±3.28)/s, respectively;R2*med/cor of the of control group, stage 1 kidney injury group and stage 2 kidney injury group were 1.67 ± 0.09, 1.75 ± 0.16, 1.63 ± 0.13, respectively, and the differences among the three groups were statistically significant (F values were 17.779, 19.170 and 3.439 , all P<0.05). Furthermore, the renal cortical and medullary R2* values of chronic hepatitis b patients were significantly higher than the control group, and the the renal cortical R2* value of the patients in stage 2 kidney injury group was also higher than the stage 1 kidney injury group. The area under curve (AUC) of ROC of the renal cortical and medullary R2*values and R2*med/cor to diagnose chronic HBV hepatitis-induced early kidney injury were 0.903, 0.949 and 0.526, respectively. Conclusion It's feasible and has great value to use renal BOLD MRI for the diagnosis of chronic hepatitis b-induced early kidney injury, and the renal cortex is more sensitive than the medulla to the kidney injury.

Metabolic characteristics of 39 human brain tumor tissues, including 15 astrocytomas, 13 fibroblastic meningiomas and 11 transitional meningiomas from 39 individual patients, have been studied using high resolution magic-angle spinning (HRMAS) 1H NMR spectroscopy in conjunction with principal component analysis (PCA). With rich metabolite information, 1H NMR spectra showed that the tumor-tissuc metabonome was dominated by lipids, lactate, myo-inositol, ereatine, choline metabolites such as choline, phosphocholine and glycerophosphocholine, amino acids such as alanine, glutamate, glutamine, taurine, N-acetyl-aspartate and glutathione. PCA of the tumor NMR spectra clearly showed metabonomic differences between low-grade astrocytomas and meningiomas whereas such differences were more moderate between fibroblastic and transitional meningiomas. Compared with meningiomas, the low-grade astrocytomas had higher levels of glycerophosphocholine, phosphocholine, myo-inositol and creatine but lower levels of alanine, glutamate, glutamine, glutathione and taurine. The N-acetyl-aspartate level was low but detectable in low-grade astrocytomas whereas it was not detectable in meningiomas. It is concluded that tissue metabonomics technology consisting of HRMAS 1H NMR spectroscopy and multivariate data analysis (MVDA) offers a useful tool (1) for distinguishing different types of brain tumors, (2) for providing the metabolic information for human brain tumors, which are potentially useful for understanding biochemistry of tumor progression.