Enzyme-Driven LC-HRMS Approach for Specific Recognition of 12α-Hydroxy Bile Acids.

The synthesis of 12α-hydroxylated bile acids (12HBAs) and non-12α-hydroxylated bile acids (non-12HBAs) occurs via classical and alternative pathways, respectively. The composition of these BAs is a crucial index for pathophysiologic assessment. However, accurately differentiating 12HBAs and non-12HBAs is highly challenging due to the limited standard substances. Here, we innovatively introduce 12α-hydroxysteroid dehydrogenase (12α-HSDH) as an enzymatic probe synthesized by heterologous expression in Escherichia coli, which can specifically and efficiently convert 12HBAs in vitro under mild conditions. Coupled to the conversion rate determined by liquid chromatography-high resolution mass spectrometry (LC-HRMS), this enzymatic probe allows for the straightforward distinguishing of 210 12HBAs and 312 non-12HBAs from complex biological matrices, resulting in a BAs profile with a well-defined hydroxyl feature at the C12 site. Notably, this enzyme-driven LC-HRMS approach can be extended to any molecule with explicit knowledge of enzymatic transformation. We demonstrate the practicality of this BAs profile in terms of both revealing cross-species BAs heterogeneity and monitoring the alterations of 12HBAs and non-12HBAs under asthma disease. We envisage that this work will provide a novel pattern to recognize the shift of BA metabolism from classical to alternative synthesis pathways in different pathophysiological states, thereby offering valuable insights into the management of related diseases.

FNICM: A New Methodology To Identify Core Metabolites Based on Significantly Perturbed Metabolic Subnetworks.

Metabolomics has emerged as a powerful tool in biomedical research to understand the pathophysiological processes and metabolic biomarkers of diseases. Nevertheless, it is a significant challenge in metabolomics to identify the reliable core metabolites that are closely associated with the occurrence or progression of diseases. Here, we proposed a new research framework by integrating detection-based metabolomics with computational network biology for function-guided and network-based identification of core metabolites, namely, FNICM. The proposed FNICM methodology is successfully utilized to uncover ulcerative colitis (UC)-related core metabolites based on the significantly perturbed metabolic subnetwork. First, seed metabolites were screened out using prior biological knowledge and targeted metabolomics. Second, by leveraging network topology, the perturbations of the detected seed metabolites were propagated to other undetected ones. Ultimately, 35 core metabolites were identified by controllability analysis and were further hierarchized into six levels based on confidence level and their potential significance. The specificity and generalizability of the discovered core metabolites, used as UC's diagnostic markers, were further validated using published data sets of UC patients. More importantly, we demonstrated the broad applicability and practicality of the FNICM framework in different contexts by applying it to multiple clinical data sets, including inflammatory bowel disease, colorectal cancer, and acute coronary syndrome. In addition, FNICM was also demonstrated as a practicality methodology to identify core metabolites correlated with the therapeutic effects of Clematis saponins. Overall, the FNICM methodology is a new framework for identifying reliable core metabolites for disease diagnosis and drug treatment from a systemic and a holistic perspective.

Targeted Quantification of Glutathione/Arginine Redox Metabolism Based on a Novel Paired Mass Spectrometry Probe Approach for the Functional Assessment of Redox Status.

Glutathione (GSH) redox control and arginine metabolism are critical in regulating the physiological response to injury and oxidative stress. Quantification assessment of the GSH/arginine redox metabolism supports monitoring metabolic pathway shifts during pathological processes and their linkages to redox regulation. However, assessing the redox status of organisms with complex matrices is challenging, and single redox molecule analysis may not be accurate for interrogating the redox status in cells and in vivo. Herein, guided by a paired derivatization strategy, we present a new ultraperformance liquid chromatography tandem mass spectrometry (UPLC-MS/MS)-based approach for the functional assessment of biological redox status. Two structurally analogous probes, 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) and newly synthesized 2-methyl-6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (MeAQC), were set for paired derivatization. The developed approach was successfully applied to LPS-stimulated RAW 264.7 cells and HDM-induced asthma mice to obtain quantitative information on GSH/arginine redox metabolism. The results suggest that the redox status was remarkably altered upon LPS and HDM stimulation. We expect that this approach will be of good use in a clinical biomarker assay and potential drug screening associated with redox metabolism, oxidative damage, and redox signaling.

Development of target-based cell membrane affinity ultrafiltration technology for a simplified approach to discovering potential bioactive compounds in natural products.

Target-based drug discovery technology based on cell membrane targets has gained significant traction and has been steadily advancing. However, current methods still face certain limitations that need to be addressed. One of the challenges is the laborious preparation process of screening materials, which can be time-consuming and resource-intensive. Additionally, there is a potential issue of non-specific adsorption caused by carrier materials, which can result in false-positive results and compromise the accuracy of the screening process. To address these challenges, this paper proposes a target-based cell membrane affinity ultrafiltration technology for active ingredient discovery in natural products. In this technique, the cell membranes of human lung adenocarcinoma epithelial cells (A549) with a high expression of epidermal growth factor receptor (EGFR) were incubated with candidate drugs and then transferred to an ultrafiltration tube. Through centrifugation, components that interacted with EGFR were retained in the ultrafiltration tube as "EGFR-ligand" complex, while the components that did not interact with EGFR were separated. After thorough washing and eluting, the components interacting with EGFR were dissociated and further identified using LC-MS, enabling the discovery of bioactive compounds. Moreover, the target-based cell membrane affinity ultrafiltration technology exhibited commendable binding capacity and selectivity. Ultimately, this technology successfully screened and identified two major components from the Curcumae Rhizoma-Sparganii Rhizoma (CS) herb pair extracts, which were further validated for their potential anti-tumor activity through pharmacological experiments. By eliminating the need for laborious preparation of screening materials and the potential non-specific adsorption caused by carriers, the development of target-based cell membrane affinity ultrafiltration technology provides a simplified approach and method for bioactive compounds discovery in natural sources.

Least absolute shrinkage and selection operator-based prediction of collision cross section values for ion mobility mass spectrometric analysis of lipids.

Collision cross section (CCS) values generated from ion mobility mass spectrometry (IM-MS) have commonly been employed to facilitate lipid identification. However, this is hindered by the limited available lipid standards. Recently, CCS values were predicted by means of computational calculations, though the prediction precision was generally not good and the predicted CCS values of the lipid isomers were almost identical. To address this challenge, a least absolute shrinkage and selection operator (LASSO)-based prediction method was developed for the prediction of lipids' CCS values in this study. In this method, an array of molecular descriptors were screened and optimized to reflect the subtle differences in structures among the different lipid isomers. The use of molecular descriptors together with a wealth of standard CCS values for the lipids (365 in total) significantly improved the accuracy and precision of the LASSO model. Its accuracy was externally validated with median relative errors (MREs) of <1.1% using an independent data set. This approach was demonstrated to allow differentiation of cis/trans and sn-positional isomers. The results also indicated that the LASSO-based prediction method could practically reduce false-positive identifications in IM-MS-based lipidomics.

Measurement of Intracellular Nitric Oxide with a Quantitative Mass Spectrometry Probe Approach.

Nitric oxide (NO) is a molecule of physiological importance, and the function of NO depends on its concentration in biological systems, particularly in cells. Concentration-based analysis of intracellular NO can provide insight into its precise role in health and disease. However, current methods for detecting intracellular NO are still inadequate for quantitative analysis. In this study, we report a quantitative mass spectrometry probe approach to measure NO levels in cells. The probe, Amlodipine (AML), comprises a Hantzsch ester group that reacts with NO to form a pyridine, Dehydro Amlodipine (DAM). Quantification of DAM by ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) allows specific measurement of intracellular NO levels. Notably, the AML/NO reaction proceeds rapidly (within 1 s), which is favorable for NO detection considering its large diffusivity and short half-life. Meanwhile, studies under simulated physiological conditions revealed that the AML response to NO is proportional and selective. The presented UPLC-MS/MS method showed high sensitivity (LLOQ = 0.24 nM) and low matrix interference (less than 15%) in DAM quantification. Furthermore, the mass spectrometry probe approach was demonstrated by enabling the measurement of endogenous and exogenous NO in cells. Hence, the quantitative UPLC-MS/MS method developed using AML as a probe is expected to be a new method for intracellular NO analysis.

In silico production of relative correction factor for the quantitative analysis of multi-components by single marker method.

INTRODUCTION: Traditional methods to derive experimentally-generated relative correction factors (RCFs) for the quantitative analysis of herbal multi-components by single marker (QAMS) method require reference standards and multiple validations with different instruments and columns, which hampers high throughput implementation. OBJECTIVES: To effectively reduce the application amounts of raw material and provide higher and more stable accuracy, this study aimed to develop a method to computationally generate RCFs of herbal components. MATERIALS AND METHODS: This strategy included the published data collection, calibration curves screening, computer algorithm-based RCFs generation and accuracy validation. RESULTS: Using the in silico approach, we have successfully produced 133 RCFs for the multi-component quantitative analysis of 63 widely used herbs. CONCLUSION: Compared with conventional RCFs, this in silico method would be a low cost and highly efficient way to produce practical RCFs for the QAMS method.

Comparative analysis and natural evolution of squalene epoxidase in three Fritillaria species.

Fritillariae Bulbus are the most commonly used antitussive and edible herbs in China. Based on UPLC-QTOF-MS and UPLC-QQQ-MS, the validated MRM-based non-targeted quantitative method was applied to determinate the contents of 48 Fritillaria alkaloids (FAs) in three Fritillaria species (F. thunbergii Miq., F. unibracteata and F. ussuriensis). The RNA-Seq results showed that gene transcript levels have different expression patterns in three Fritillaria species. Based on transcriptome data, the full-length cDNA sequences of squalene epoxidase gene were cloned and characterized. Natural evolution of squalene epoxidase genes resulted in four mutations (C236R, M489L, G510A and K517R) in three Fritillaria species. Molecular docking analysis showed that the 236 residue is located inside the pocket and the binding center while other three residues are located on the surface of the protein. Functional verification indicated the mutations of SQE (C236R) could effectively increase the activity of SQE and obtain higher yield of 2,3-oxidosqualene in recombinant yeast. And the mutations of SQE (M489L and G510A), which increased the hydrophobicity of the protein surface, could also enhance the activity of SQE. This study provides major insights into the metabolites differentiation of FAs biosynthesis, and a firm foundation for the quality control and metabolic engineering of Fritillariae bulbus.

Saponins from Clematis mandshurica Rupr. regulates gut microbiota and its metabolites during alleviation of collagen-induced arthritis in rats.

Gut microbiota and their metabolites (short-chain fatty acids, SCFAs) are associated with the pathogenesis of rheumatoid arthritis (RA). Total Clematis triterpenoid saponins (CTSs) prepared from Clematis mandshurica Rupr. possess therapeutic benefits for arthritic diseases. However, the poor pharmacokinetic properties of CTSs have obstructed the translation of these natural agents to drugs. Here, we examined the effects of CTSs on arthritis symptoms, gut microbiota and SCFAs in rats with collagen-induced arthritis (CIA). Our results showed that the arthritis index scores of CIA rats treated with CTSs were significantly lower than those of the model group. Most importantly, CTSs moderated gut microbial dysbiosis and significantly downregulated the total SCFA concentration in CIA rats. Compared to the control group, CTSs treatment have no significant side effects on the gut microbiota and SCFA metabolism in normal rats. Two differential analyses (LEfSe and DESeq2) were combined to study the details of the changes in gut microbiome, and twenty-four marker taxa at the genus level were identified via a comparison among control, model and CIA rats treated with high doses of CTSs. In particular, the mostly significantly increased gram-negative (G-) and decreased gram-positive (G+) genera in CIA rats were well restored by CTSs. The observed SCFA concentrations demonstrated that CTSs tend to maintain the balance of the gut microbiota. The data presented herein suggest that CTSs could ameliorate arthritis-associated gut microbial dysbiosis and may be potential adjuvant drugs that could provide relief from the gastrointestinal damage caused as a side effect of commonly used drugs.

Global detection and semi-quantification of Fritillaria alkaloids in Fritillariae Ussuriensis Bulbus by a non-targeted multiple reaction monitoring approach.

Methods based on triple quadrupole tandem mass spectrometry have been widely used and reported as highly selective and sensitive methods for quantifying substances of herbal medicines. However, most of them were limited to targeted components, due to the difficulties to optimize the multiple reaction monitoring transitions without authentic standards. This study proposed a novel strategy for non-targeted optimization of multiple reaction monitoring method based on the diagnostic ion guided family classifications, tandem mass spectrometry database establishment, and transitions and collision energy screening. Applying this strategy, 59 Fritillaria alkaloids in Fritillariae Ussuriensis Bulbus have been classified, and 51 of these Fritillaria alkaloids were successfully detected by the optimal multiple reaction monitoring method. For semi-quantification, the easy-to-obtain Fritillaria alkaloids of each type, such as verticinone for cevanine type and peimisine for jervine type, were used as the reference standards to calibrate the other Fritillaria alkaloids in the same type. The method was demonstrated a good linearity (R(2) > 0.998) with satisfactory accuracy and precision, and the lower limits of quantification of verticinone and peimisine were estimated to be 0.076 and 0.216 pg, respectively. In addition, the results suggested that the proposed strategy might obtained high quality metabolomics data in discrimination of Fritillaria unibracteata and Fritillaria ussuriensis.

Authentication of Cordyceps sinensis by DNA Analyses: Comparison of ITS Sequence Analysis and RAPD-Derived Molecular Markers.

Cordyceps sinensis is an endoparasitic fungus widely used as a tonic and medicinal food in the practice of traditional Chinese medicine (TCM). In historical usage, Cordyceps specifically is referring to the species of C. sinensis. However, a number of closely related species are named themselves as Cordyceps, and they are sold commonly as C. sinensis. The substitutes and adulterants of C. sinensis are often introduced either intentionally or accidentally in the herbal market, which seriously affects the therapeutic effects or even leads to life-threatening poisoning. Here, we aim to identify Cordyceps by DNA sequencing technology. Two different DNA-based approaches were compared. The internal transcribed spacer (ITS) sequences and the random amplified polymorphic DNA (RAPD)-sequence characterized amplified region (SCAR) were developed here to authenticate different species of Cordyceps. Both approaches generally enabled discrimination of C. sinensis from others. The application of the two methods, supporting each other, increases the security of identification. For better reproducibility and faster analysis, the SCAR markers derived from the RAPD results provide a new method for quick authentication of Cordyceps.

Authentication of Bulbus Fritillariae Cirrhosae by RAPD-derived DNA markers.

Bulbus Fritillariae is the most commonly used antitussive herb in China. Eleven species of Fritillaria are recorded as Bulbus Fritillariae in the Chinese Pharmacopoeia. Bulbus Fritillariae Cirrhosae is a group of six Fritillaria species with higher efficiency and lower toxicity derived mainly from wild sources. Because of their higher market price, five other Fritillaria species are often sold deceptively as Bulbus Fritillariae Cirrhosae in the herbal market. To ensure the efficacy and safety of medicinal herbs, the authentication of botanical resources is the first step in quality control. Here, a DNA based identification method was developed to authenticate the commercial sources of Bulbus Fritillariae Cirrhosae. A putative DNA marker (0.65 kb) specific for Bulbus Fritillariae Cirrhosae was identified using the Random Amplified Polymorphic DNA (RAPD) technique. A DNA marker representing a Sequence Characterized Amplified Region (SCAR) was developed from a RAPD amplicon. The SCAR marker was successfully applied to differentiate Bulbus Fritillariae Cirrhosae from different species of Fritillaria. Additionally, the SCAR marker was also useful in identifying the commercial samples of Bulbus Fritillariae Cirrhosae. Our results indicated that the RAPD-SCAR method was rapid, accurate and applicable in identifying Bulbus Fritillariae Cirrhosae at the DNA level.

Comprehensive exploration of a traditional Chinese medicinal plant of Magnolia officinalis based on high-coverage mass spectrometry and multidimensional chemical-biological analysis.

Magnolia bark is a traditional Chinese medicine used for hypoglycaemia. With the widespread use of Magnolia bark, its resources are facing a serious shortage. To address this issue, a strategy based on high-coverage mass spectrometry (HCMS) and multidimensional chemical-biological analysis (MCBA) was proposed for the comprehensive exploration of Magnolia officinalis which is the main source of Magnolia bark. The strategy is divided into three main steps. In the first step, the stem bark, stem xylem, root bark, root xylem, leaf and rootlet of Magnolia officinalis were comprehensively analyzed using high-coverage mass spectrometry. In the second step, multivariate statistical analysis was used to explore the heterogeneity of the six parts and detect differential chemical components. In the third step, a combination of experimental screening and molecular docking was used to explore α-glucosidase inhibitors from Magnolia officinalis. Multidimensional chemical-biological analysis (MCBA) of Magnolia officinalis was achieved by combining the last two steps. Finally, a total of 103 compounds were identified from the whole plant of Magnolia officinalis. Differential components of stem bark, stem xylem, leaf, root bark, root xylem and rootlet were systematically revealed. A pair of positional isomers, namely magnolol and honokiol, were found to be α-glucosidase inhibitors. The activity of their combination is superior to that of each single compound, indicating that magnolol and honokiol are in a synergistic relationship. This strategy contributes to comprehensive exploitation of functional plants and effective alleviation of resource shortage. This study also provides a research paradigm for other similar traditional Chinese medicinal plants.

Integration of High-Resolution LC-Q-TOF Mass Spectrometry and Multidimensional Chemical-Biological Analysis to Detect Nanomolar-Level Acetylcholinesterase Inhibitors from Different Parts of Zanthoxylum nitidum.

Zanthoxyli radix is a popular tea among the elderly, and it is believed to have a positive effect on Alzheimer's disease. In this study, a highly effective three-step strategy was proposed for comprehensive analysis of the active components and biological functions of Zanthoxylum nitidum (ZN), including high-resolution LC-Q-TOF mass spectrometry (HRMS), multivariate statistical analysis for heterogeneity (MSAH), and experimental and virtual screening for bioactivity analysis (EVBA). A total of 117 compounds were identified from the root, stem, and leaf of ZN through HRMS. Bioactivity assays showed that the order of acetylcholinesterase (AChE) inhibitory activity from strong to weak was root > stem > leaf. Nitidine, chelerythrine, and sanguinarine were found to be the main differential components of root, stem, and leaf by OPLS-DA. The IC50 values of the three compounds are 0.81 ± 0.02, 0.14 ± 0.01, and 0.48 ± 0.01 µM respectively, indicating that they are potent and high-quality AChE inhibitors. Molecular docking showed that pi-pi T-shaped interactions and pi-lone pairs played important roles in AChE inhibition. This study not only explains the biological function of Zanthoxyli radix in alleviating Alzheimer's disease to some extent, but also lays the foundation for the development of stem and leaf of ZN.

Pseudotargeted metabolomics-based random forest model for tracking plant species from herbal products.

BACKGROUND: The "one-to-multiple" phenomenon is prevalent in medicinal herbs. Accurate species identification is critical to ensure the safety and efficacy of herbal products but is extremely challenging due to their complex matrices and diverse compositions. PURPOSE: This study aimed to identify the determinable chemicalome of herbs and develop a reasonable strategy to track their relevant species from herbal products. METHODS: Take Astragali Radix-the typical "one to multiple" herb, as a case. An in-house database-driven identification of the potentially bioactive chemicalome (saponins and flavonoids) in AR was performed. Furthermore, a pseudotargeted metabolomics method was first developed and validated to obtain high-quality semi-quantitative data. Then based on the data matrix, the random forest algorithm was trained to predict Astragali Radix species from commercial products. RESULTS: The pseudotargeted metabolomics method was first developed and validated to obtain high-quality semi-quantitative data (including 56 saponins and 49 flavonoids) from 26 batches of AR. Then the random forest algorithm was well-trained by importing the valid data matrix and showed high performance in predicting Astragalus species from ten commercial products. CONCLUSION: This strategy could learn species-special combination features for accurate herbal species tracing and could be expected to promote the traceability of herbal materials in herbal products, contributing to manufacturing standardization.

Targeting tryptophan metabolism reveals Clematichinenoside AR alleviates triptolide-induced hepatotoxicity.

Liver toxicity induced by Triptolide (TP) has limited its clinical application on rheumatoid arthritis (RA). Saponins have been proved as an efficacious remedy to mitigate hepatotoxicity. However, the mechanism of reducing hepatotoxicity by saponins intervention remains incompletely characterized. Tryptophan (Trp) metabolites activate transcriptional regulators to mediate host detoxification responses. Our study aimed to investigate whether Clematichinenoside AR (C-AR) could attenuate TP-induced liver damage by regulating Trp metabolism. We used targeted metabolomics to quantify Trp metabolites in the serum and liver samples of collagen-induced arthritis rats treated by TP. Multiple comparison analyses helped the evaluation of promising biomarkers. The pronounced changed levels of Trp, indole acetic acid, and indole-3-carboxaldehyde in the serum and indole acetic acid, indole, and tryptamine in the liver are relevant to TP-induced liver injury. Intervention with C-AR could relieve TP-induced hepatotoxicity evidenced by ameliorative serum parameters and hepatic histology. In addition, C-AR regulated the levels of these indoles biomarker candidates to normal. Therapeutic modulation with natural compounds might be a useful clinical strategy to ameliorate toxicity induced by TP. Deciphering Trp metabolism will facilitate a better understanding of the pathogenesis of diseases and drug responding.

An in-house database-driven untargeted identification strategy for deep profiling of chemicalome in Chinese medicinal formula.

Deep profiling of chemicalome in Chinese medicinal formulas is vital for disclosing the secret underlying their effectiveness. To address this issue, an in-house database-driven untargeted identification strategy was proposed with the use of ultra-performance liquid chromatography coupled to quadrupole time of flight mass spectrometry. Firstly, an in-house mass spectral database for the analyzed herbs was constructed, and database querying was performed for rapid recognition of known compounds. Secondly, a chemical diagnostic characteristics algorithm was originally developed for deep mining unrecorded ions, and thus expanding coverage of components beyond the database. Additionally, we proposed evaluation criteria for the untargeted identification of compounds with different confidence levels. As a case study, the integrated strategy was applied to comprehensively characterize complex multi-type components in Gegen-Qinlian Decoction. A total of 381 compounds were characterized and annotated with four different confidence levels, and 88.40% of these annotated compounds were successfully re-identified in triplicate analyses with a different instrument. The integrated strategy was demonstrated powerful in deep profiling of chemicalome in Chinese medicinal formulas with higher throughput, analytical sharpness, and lower omission ratios.

Lipidomics characterization of the mechanism of Cynomorium songaricum polysaccharide on treating type 2 diabetes.

Although Cynomorium songaricum Rupr. polysaccharide (CSP) has been examined for its effects on glucose regulation, its underlying mechanism is still unclear. To address this issue, a MS-based lipidomics strategy was developed to gain a system-level understanding of the mechanism of CSP on improving type 2 diabetes mellitus (T2DM). UPLC-QTOF/MS and multivariate statistical tools were used to identify the alteration of serum metabolites associated with T2DM and responses to CSP treatment. As a result, 35 potential biomarkers were found and identified in serum, amongst which 26 metabolites were regulated to normal like levels after the administration of CSP. By analyzing the metabolic pathways, glycerophospholipid metabolism was suggested to be closely involved. These results indicated that the intake of CSP exhibited promising anti-diabetic activity, largely due to the regulation of phospholipid metabolism, including phosphatidylcholines, lysophosphatydylcholines, phosphtatidylethanolamines and sphingomyelins.

Mesoporous silica-mediated controllable electrochemiluminescence quenching for immunosensor with simplicity, sensitivity and tunable detection range.

Straightforward and accurate measurement of medical biomarkers is of essential importance in clinical diagnostics and treatments. However, the major challenge is the diversity in dynamic range of different biomarkers ranging from pg mL-1 to µg mL-1 in various body fluids and tissues among patients. Here, we develop a mesoporous silica (MS)-mediated controllable electrochemiluminescence (ECL) quenching of immunosensor that allows accurate immunoassays with simplicity, sensitivity and tunable sensing range. MS is employed to enhance the sensitivity and tune ECL quenching to broaden the detection range just by altering luminophore (Ru(bpy)32+) and coreactant (DBAE) concentration without additional modifications. The immunoassay is followed: homogeneous sandwich immunoreaction, magnetic separation, and ECL quenching detection. As a proof-of-concept, simple and sensitive detection of IgG is achieved ranging from pg mL-1 to µg mL-1, and applications of the strategy are extended by the combination of ECL immunosensor with commercial ELISA kit. This study will not only be expected to serve as a new avenue for the assay of physiological and clinical implications of immunological biomarkers, but also benefit a wide range of applications that require a tunable detection range and ultrahigh sensitivity.

miR122-controlled all-in-one nanoplatform for in situ theranostic of drug-induced liver injury by visualization imaging guided on-demand drug release.

Drug-induced liver injury (DILI) is a challenging clinical problem with respect to both diagnosis and management. As a newly emerging biomarker of liver injury, miR122 shows great potential in early and sensitive in situ detection of DILI. Glycyrrhetinic acid (GA) possesses desirable therapeutic effect on DILI, but its certain dose-dependent side effects after long-term and/or high-dose administration limit its clinical application. In this study, in order to improve the precise diagnosis and effective treatment of DILI, GA loaded all-in-one theranostic nanoplatform was designed by assembling of upconversion nanoparticles and gold nanocages. As a proof of concept, we demonstrated the applicability of this single-wavelength laser-triggered theranostic nanoplatform for the spatiotemporally controllable in situ imaging of DILI and miR122-controlled on-demand drug release in vitro and in vivo. This novel nanoplatform opens a promising avenue for the clinical diagnosis and treatment of DILI.