Strategy to Empower Nontargeted Metabolomics by Triple-Dimensional Combinatorial Derivatization with MS-TDF Software.

Chemical derivatization is a widely employed strategy in metabolomics to enhance metabolite coverage by improving chromatographic behavior and increasing the ionization rates in mass spectroscopy (MS). However, derivatization might complicate MS data, posing challenges for data mining due to the lack of a corresponding benchmark database. To address this issue, we developed a triple-dimensional combinatorial derivatization strategy for nontargeted metabolomics. This strategy utilizes three structurally similar derivatization reagents and is supported by MS-TDF software for accelerated data processing. Notably, simultaneous derivatization of specific metabolite functional groups in biological samples produced compounds with stable but distinct chromatographic retention times and mass numbers, facilitating discrimination by MS-TDF, an in-house MS data processing software. In this study, carbonyl analogues in human plasma were derivatized using a combination of three hydrazide-based derivatization reagents: 2-hydrazinopyridine, 2-hydrazino-5-methylpyridine, and 2-hydrazino-5-cyanopyridine (6-hydrazinonicotinonitrile). This approach was applied to identify potential carbonyl biomarkers in lung cancer. Analysis and validation of human plasma samples demonstrated that our strategy improved the recognition accuracy of metabolites and reduced the risk of false positives, providing a useful method for nontargeted metabolomics studies. The MATLAB code for MS-TDF is available on GitHub at https://github.com/CaixiaYuan/MS-TDF.

Chemical proteomics unveils that seventy flavors pearl pill ameliorates ischemic stroke by regulating oxidative phosphorylation.

Ischemic stroke has high mortality and morbidity rates and is the second leading cause of death in the world, but there is no definitive medicine. Seventy Flavors Pearl Pill (SFPP) is a classic formula in Tibetan Medicine. Clinical practice has shown the attenuation effect of SFPP on blood pressure disorders, strokes and their sequelae and other neurological symptoms, but its mechanism remains to be elucidated. In this study, we established three animal models in vivo and three cell models to evaluate the anti-hypoxia, anti-ischemia, and reperfusion injury prevention effects of SFPP. Quantitative proteomics revealed that oxidative phosphorylation (OXPHOS) is essential for SFPP's efficacy. Then, cysteine-activity based protein profiling technology, which reflects redox stress at the proteome level, was employed to illustrate that SFPP brought functional differences of critical proteins in OXPHOS. In addition, quantitative metabolomics revealed that SFPP affects whole energy metabolism with OXPHOS as the core. Finally, we performed a compositional identification of SFPP to initially explore the components of potential interventions in OXPHOS. These results provide new perspectives and tools to explore the mechanism of herbal medicine. The study suggests that OXPHOS could be a potential target for further research and intervention of ischemic stroke treatment.

Liposomal doxorubicin and free doxorubicin in vivo quantitation method developed on CE-LIF and its application in pharmacokinetic analysis.

As a novel drug delivery system, liposomes were used to improve pharmacokinetics/pharmacodynamics (PK/PD) characters, minimize toxicity, and enhance drug-target selectivity. However, heterogeneity of drug releasing process and liposome itself challenged traditional pharmaceutical analytical techniques, especially in vivo pharmacokinetic studies. In this study, a novel liposomal doxorubicin (L-DOX) pharmacokinetic analysis strategy was developed with capillary electrophoresis coupled with laser-induced fluorescence (CE-LIF) detector. The background electrolyte (BGE) system was composed of borate and sodium dodecyl sulfate (SDS), which was optimized to successfully achieve simultaneous online separation and quantitative analysis of free DOX and liposome-encapsulated DOX. The method was applied to the in vivo pharmacokinetic study of L-DOX in rats. The results showed that the concentration of total DOX (T-DOX) was gradually decreasing, while the concentration of L-DOX was relatively stable, with a concentration of 31.6 ± 4.8 µg/mL within 24 h. It was the first time to achieve liposomal drugs in vivo analysis with CE-LIF. CE-LIF was proved as potential rapidly real-time analytical methods for liposomal drugs in vivo occurrence monitoring.

MS-IDF: A Software Tool for Nontargeted Identification of Endogenous Metabolites after Chemical Isotope Labeling Based on a Narrow Mass Defect Filter.

Chemical isotope labeling liquid chromatography mass spectrometry (LC-MS) is an emerging metabolomic strategy for the quantification and characterization of small molecular compounds in biological samples. However, its subsequent data analysis is not straightforward due to a large amount of data produced and interference of biological matrices. In order to improve the efficiency of searching and identification of target endogenous metabolites, a new software tool for nontargeted metabolomics data processing called MS-IDF was developed based on the principle of a narrow mass defect filter. The developed tool provided two function modules, including IsoFinder and MDFinder. The IsoFinder function module applied a conventional peak extraction method by using a fixed mass differences between the heavy and light labels and by the alignment of chromatographic retention time (RT). On the other hand, MDFinder was designed to incorporate the accurate mass defect differences between or among stable isotopes in the peak extraction process. By setting an appropriate filter interval, the target metabolites can be efficiently screened out while eliminating interference. Notably, the present results showed that the efficiency in compound identification using the new MDFinder module was nearly doubled as compared to the conventional IsoFinder method (an increase from 259 to 423 compounds). The Matlab codes of the developed MS-IDF software are available from github at https://github.com/jydong2018/MS_IDF. Based on the MS-IDF software tool, a novel and effective approach from nontargeted to targeted metabolomics research was developed and applied to the exploration of potential primary amine biomarkers in patients with schizophrenia. With this approach, potential biomarkers, including N,N-dimethylglycine, S-adenosine-l-methionine, dl-homocysteine, and spermidine, were discovered.

Rapid Simultaneous Determination of 14 Antidepressants and 13 Antipsychotics in Human Plasma by Using High-Performance Liquid Chromatography-Tandem Mass Spectrometry With Dynamic Multiple Reaction Monitoring and Its Application to Therapeutic Drug Monitoring.

BACKGROUND: A comprehensive, stable, and efficient high-performance liquid chromatography-tandem mass spectrometry method was developed for rapidly analyzing 14 antidepressants and 13 antipsychotics in human plasma for routine clinical therapeutic drug monitoring. METHODS: Simple protein precipitation was used for the pretreatment of plasma samples; dynamic multiple reaction monitoring was used to avoid the loss of sensitivity caused by numerous ion transitions. In all, 80 ion transitions of 40 compounds were quantitatively determined in 6 minutes. RESULTS: The limit of detection for the 27 analytes was in the range of 0.1-30 ng/mL, and all calibration lines prepared using blank plasma were linear with a correlation coefficient of r2 ≥ 0.99. The method was accurate and precise with acceptable intraday and interday precisions (coefficients of variation, ≤20% for a lower limit of quantification and ≤15% for other quality control samples) and an accuracy of 85.51%-114.77%. This analysis method has been completely validated and successfully used in routine clinical therapeutic drug monitoring for more than 9963 samples [including 488 samples having drug concentrations above the laboratory alert level (supra-alert-level samples)] at Xiamen Xianyue Hospital. CONCLUSIONS: This dynamic method is comprehensive (includes most antidepressants and antipsychotics listed in China), reliable (stably used for almost 2 years), and efficient (convenient sample processing and short run time) and provides a large amount of meaningful data for optimized pharmacotherapy. Our experimental data from the plasma concentrations of supra-alert-level samples could serve as a reference for the interpretation of the pharmacokinetics of patients with a high risk of toxicity or loss of tolerability.

Artificial intelligence and network pharmacology based investigation of pharmacological mechanism and substance basis of Xiaokewan in treating diabetes.

Xiaokewan is a typical Traditional Chinese medicine (TCM) for diabetes and contains various natural chemicals, such as lignans, flavonoids, saponins, polysaccharides, and western medicine glibenclamide. In the current study, a highly efficient system for screening hypoglycemic efficacy constituents of Xiaokewan has been developed with the integration of intelligent data acquisition, data mining, network pharmacology, and computer assisted target fishing. With the combination of background exclusion data dependent acquisition (BE-DDA) and non-targeted precise-and-thorough background-subtraction (PATBS) techniques, a novel workflow has been established for the non-targeted recognition and identification of TCM constituents in vivo, and has been applied to the exposure study of Xiaokewan in rat. In this case, an interesting correlation among drug, target, and disease can be established, by combining the screening or characterization results with the strategy of network pharmacology and multiple computer assisted techniques. Consequently, five main constituents (puerarin, daidzein, formononetin, deoxyschizandrin and glibenclamide) exposed in vivo have been selected as effective hypoglycemic components. Meanwhile, the network pharmacology experimental results showed that these five constituents could act on various drug targets, such as PI3K, PTP1B, MAPK, AKT, TNF, and NF-κB. These five constituents might be involved in the regulation of ß-cell function or exhibit inflammation inhibition ability to relieve the pathophysiological process of disease from multiple links. Furthermore, the pharmacological effects of these five constituents have been verified by diabetic zebrafish model. The zebrafish model results showed that the TCM monomer mixture without glibenclamide exhibited similar hypoglycemic activity with Xiaokewan. Although the monomer mixture with glibenclamide showed better activity than Xiaokewan only, the deoxyschizandrin (TCM constituent of Xiaokewan) exhibited best hypoglycemic performance. In summary, the above results indicated that the application of both intelligent recognition technology in mass spectrometry dataset and computerized network pharmacology might provide a pioneering approach for investigating the substance basis of TCM and searching lead compounds from natural sources.

Rapid detection and structural characterization of verapamil metabolites in rats by UPLC-MSE and UNIFI platform.

High-resolution mass spectrometry (HRMS) is an important technology for studying biotransformations of drugs in biological systems. In order to process complex HRMS data, bioinformatics, including data-mining techniques for identifying drug metabolites from liquid chromatography/high-resolution mass spectrometry (LC/HRMS) or multistage mass spectrometry (MSn ) datasets as well as elucidating the detected metabolites' structure by spectral interpretation software, are important tools. Data-mining technologies have widely been used in drug metabolite identification, including mass defect filters, product ion filters, neutral-loss filters, control sample comparisons and extracted ion chromatographic analysis. However, the metabolites identified by current different technologies are not the same, indicating the importance of technique integration for efficient and complete identification of metabolic products. In this study, a universal, high-throughput workflow for identifying and verifying metabolites by applying the drug metabolite identification software UNIFI is reported, to study the biotransformation of verapamil in rats. A total of 71 verapamil metabolites were found in rat plasma, urine and faeces, including two metabolites that have not been reported in the literature. Phase I metabolites of verapamil were identified as N-demethylation, O-demethylation, N-dealkylation and oxidation and dehydrogenation metabolites; phase II metabolites were mainly glucuronidation and sulfate conjugates, indicating that UNIFI software could be effective and valuable in identifying drug metabolites.

Simultaneous determination of VD2, VD3, 25(OH) D2, and 25(OH) D3 in human plasma using electrospray LC-MS/MS as well as its application to evaluate VD plasma levels in depressive, schizophrenic patients and healthy individuals.

Vitamin D measurements in biological fluids by liquid chromatography-tandem mass spectrometry (LC-MS/MS) have been widely used but remain challenging at very low concentration levels. Rapid, high recovery, sensitive and reliable measurements of vitamin D, as well as its primary metabolites using LC-MS/MS are urgently needed for a routine clinical laboratory. Herein, we reported a novel electrospray LC-MS/MS method for determining vitamin D and its primary metabolites using the supported liquid extraction method to achieve higher recoveries, with optimized pH values to achieve optimal derivatization efficiency for higher sensitivity and selected chromatographic conditions to shorten the separation time. The method has been validated with respect to selectivity, recovery, matrix effects, accuracy and precision, stabilities, carryover and dilution effects. The method has been successfully applied to quantify the VD plasma concentrations of depressive, schizophrenic patients and healthy individuals. The result showed that there were significant differences in plasma VD levels between mental disorder patients with healthy individuals, and the total VD levels in mental disorder patients were much higher than healthy individuals, which might require larger clinical samples for validation.

Cyclodextrin-Based Star-Like Amphiphilic Cationic Polymer as a Potential Pharmaceutical Carrier in Macrophages.

Effective delivery of therapeutic genes or small molecular drugs into macrophages is important for cell based immune therapy, but it remains a challenge due to the intracellular reactive oxygen species and endosomal degradation of therapeutics inside immune cells. In this report, the star-like amphiphilic biocompatible ß-cyclodextrin-graft-(poly(ε-caprolactone)-block-poly(2-(dimethylamino) ethyl methacrylate)x (ß-CD-g-(PCL-b-PDMAEMA)x ) copolymer, consisting of a biocompatible cyclodextrin core, hydrophobic poly(ε-caprolactone) PCL segments and hydrophilic PDMAEMA blocks with positive charge, is optimized to achieve high efficiency gene transfection with enhanced stability, due to the micelle formation by hydrophobic PCL segments. In comparison with lipofetamine, a currently popular nonviral gene carrier, ß-CD-g-(PCL-b-PDMAEMA)x copolymer, shows better transfection efficiency of plasmid desoxyribose nucleic acid in RAW264.7 macrophages. More interestingly, this delivery platform by ß-CD-g-(PCL-b-PDMAEMA)x not only shows low toxicity but also better dexamethasone delivery efficiency, which might indicate its great potential in immunotherapy.

Ultraperformance Liquid Chromatography-Tandem Mass Spectrometry Method for Profiling Ketolic and Phenolic Sex Steroids Using an Automated Injection Program Combined with Diverter Valve Switch and Step Analysis.

Sex steroids are involved in many physiological and pathological processes. The determination of sex steroids is essential to understand the mechanisms of human health and diseases. Derivatization techniques could specifically enhance the sensitivities for sex steroids with a given functional group. However, no derivatization reagents are available for profiling multifunctional sex steroids, including phenolic estrogens, ketolic androgens, and ketolic progestogens, in a single analytical run. In the present study, a novel method involving ultraperformance liquid chromatography coupled with triple quadrupole mass spectrometry (UPLC-MS/MS) was developed for profiling both ketolic and phenolic sex steroids in human serum using an automated injection program combined with diverter valve switch and step analysis (AIDSA). The human serum, prepared through liquid-liquid extraction and subsequently derivatized using Girard P offline, was automatically injected twice under the automated injection program. For the first injection, Girard P-derivatized ketolic sex steroids were loaded onto the column, and subsequently, the second injection and online derivatization of the same sample using dansyl chloride were performed in the injector needle for 15 min. The dansyl-labeled phenolic sex steroids were then loaded onto the column. The diverter valve worked in coordination with the injection program to import the derivatized sex steroids and remove excess derivatization reagents. The two types of derivatives were individually analyzed in a step-by-step manner. In addition, online dansyl derivatization and Girard P derivative analyses were simultaneously implemented to shorten the total analysis time. This method was well validated and applied to determine the sex steroid levels in human serum.

An Integrated Approach for Studying Exposure, Metabolism, and Disposition of Multiple Component Herbal Medicines Using High-Resolution Mass Spectrometry and Multiple Data Processing Tools.

A typical prescription of traditional Chinese medicine (TCM) contains up to a few hundred prototype components. Studying their absorption, metabolism, distribution, and elimination (ADME) presents great challenges. The objective of this study was to develop a practical approach for investigating ADME of individual prototypes in TCM. An active fraction of Xiao-Xu-Ming decoction (AF-XXMD) as a model TCM prescription was orally administered to rats. AF-XXMD-related components in plasma, urine, bile, and feces were detected using high-resolution mass spectrometry and background subtraction, an untargeted data-mining tool. Components were then structurally characterized on the basis of MS(n) spectral data. Connection of detected AF-XXMD metabolites to their precursor species, either prototypes or upstream metabolites, were determined on the basis of mass spectral similarity and the matching of biotransformation reactions. As a result, 247 AF-XXMD-related components were detected and structurally characterized in rats, 134 of which were metabolites. Among 198 AF-XXMD prototypes dosed, 65 were fully or partially absorbed and 13 prototypes and 34 metabolites were found in the circulation. Glucuronidation, isomerization, and deglycosylation followed by biliary and urinary excretions and direct elimination of prototypes via kidney and liver were the major clearance pathways of AF-XXMD prototypes. As an example, the ADME profile of H56, the single major AF-XXMD component in rat plasma, was elucidated on the basis of profiles of H56-related components in plasma and excreta. The results demonstrate that the new analytical approach is a useful tool for rapid and comprehensive detection and characterization of TCM components in biologic matrix in a TCM ADME study.

Permeability of blood-brain barrier in macaque model of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced Parkinson disease.

Brain bioavailability of drugs developed to address central nervous system diseases is classically documented through cerebrospinal fluid collected in normal animals, i.e., through an approximation as there are fundamental differences between cerebrospinal fluid and tissue contents. The fact that disease might affect brain availability of drugs is almost never considered at this stage although several conditions are associated with blood-brain barrier damage. Building upon our expertise in Parkinson's disease translational research, the present study addressed this gap comparing plasma and cerebrospinal fluid bioavailability of l-3,4-dihydroxyphenylalanine, carbamazepine, quinidine, lovastatin, and simvastatin, in healthy and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-treated macaques, the gold standard model of Parkinson's disease. The drugs were selected based upon their differential transport across the blood-brain barrier. Interestingly, brain bioavailability of quinidine was decreased while others were unaffected. Pharmacokinetics and pharmacodynamics experiments of drugs addressing Parkinson's disease might thus be performed in healthy animals unless the drugs are known to interact with the organic cation transporter.

Novel strategy for the determination of illegal adulterants in health foods and herbal medicines using high-performance liquid chromatography with high-resolution mass spectrometry.

The detection, confirmation, and quantification of multiple illegal adulterants in health foods and herbal medicines by using a single analytical method are a challenge. This paper reports on a new strategy to meet this challenge by employing high-performance liquid chromatography coupled with high-resolution mass spectrometry and a mass spectral tree similarity filter technique. This analytical method can rapidly collect high-resolution, high-accuracy, optionally multistage mass data for compounds in samples. After a preliminary screening by retention time and high-resolution mass spectral data, known illegal adulterants can be detected. The mass spectral tree similarity filter technique has been applied to rapidly confirm these adulterants and simultaneously discover unknown ones. By using full-scan mass spectra as stem and data-dependent subsequent stage mass spectra to form branches, mass spectrometry data from detected compounds are converted into mass spectral trees. The known or unknown illegal adulterants in the samples are confirmed or discovered based on the similarity between their mass spectral trees and those of the references in a library, and they are finally quantified against standard curves. This new strategy has been tested by using 50 samples, and the illegal adulterants were rapidly and effectively detected, confirmed and quantified.

Identification of the chemical components of Saussurea involucrata by high-resolution mass spectrometry and the mass spectral trees similarity filter technique.

RATIONALE: Saussurea involucrata is a rare traditional Chinese medicine (TCM) that displays anti-fatigue, anti-inflammatory and anti-tumor effects. In this paper, the different chemical components of Saussurea involucrata were characterized and identified over a wide dynamic range by high-performance liquid chromatography coupled with high-resolution hybrid mass spectrometry (HPLC/HRMS/MS(n)) and the mass spectral trees similarity filter (MTSF) technique. METHODS: The aerial parts of Saussurea involucrata were extracted with 75% ethanol. The partial extract was separated on a chromatography column to concentrate the low-concentration compounds. Mass data were acquired using full-scan mass analysis (resolving power 50,000) with data-dependent incorporation of dynamic exclusion analysis. The identified compounds were used as templates to construct a database of mass spectral trees. Data for the unknown compounds were matched with those templates and matching candidate structures were obtained. RESULTS: The detected compounds were characterized based on matching to candidate structures by the MTSF technique and were further identified by their accurate mass weight, multiple-stage analysis and fragmentation patterns and through comparison with literature data. A total of 38 compounds were identified including 19 flavones, 11 phenylpropanoids and 8 sphingolipids. Among them, 7 flavonoids, 8 phenylpropanoids and 8 sphingolipids were identified for the first time in Saussurea involucrata. CONCLUSIONS: HPLC/HRMS/MS(n) combined with MTSF was successfully used to discover and identify the chemical compounds in Saussurea involucrata. The results indicated that this combined technique was extremely useful for the rapid detection and identification of the chemical components in TCMs.

Lipidomic profiling of plasma in patients with chronic hepatitis C infection.

Chronic hepatitis C virus (HCV) infection is a global health issue. Although its progression is reported to be closely associated with lipids, the way in which the plasma lipidome changes during the development of chronic HCV infection in humans is currently unknown. Using an improved quantitative high-throughput lipidomic platform, we profiled 284 lipids in human plasma samples obtained from healthy controls (n = 11) and patients with chronic HCV infection (n = 113). The intrahepatic inflammation grade (IG) of liver tissue was determined by biopsy. Two types of mass spectrometers were integrated into a single lipidomic platform with a wide dynamic range. Compared with previous methods, the performance of this method was significantly improved in terms of both the number of target sphingolipids identified and the specificity of the high-resolution mass spectrometer. As a result, 44 sphingolipids, one diacylglycerol, 43 triglycerides, 24 glycerophosphocholines, and 5 glycerophospho-ethanolamines were successfully identified and quantified. The lipid profiles of individuals with chronic HCV infection were significantly different from those of healthy individuals. Several lipids showed significant differences between mild and severe intrahepatic inflammation grades, indicating that they could be utilized as novel noninvasive indicators of intrahepatic IG. Using multivariate analysis, healthy controls could be discriminated from HCV patients based on their plasma lipidome; however, patients with different IGs were not well discriminated. Based on these results, we speculate that variations in lipid composition arise as a result of HCV infection, and are caused by HCV-related digestive system disorders rather than progression of the disease.

Metabolic studies of four soy isoflavones in rats by HPLC-HR-MS.

In this paper, the metabolites of four soy isoflavones, daidzein, daidzin, genistein, and genistin, on perfused rat intestine-liver model were investigated by high-performance liquid chromatography coupled with high-resolution mass spectrometer/tandem mass spectrometer. Totally 16 metabolites were detected and identified based on accurate mass, fragmentation patterns, and multiple-stage mass data (MS(n)). The metabolic site of dadzein-7-methyl ether (D-7-M) was further confirmed by nuclear magnetic resonance. Methylation, glucuronide conjugation, and sulfate conjugation were the primary metabolic processes. Among them, six metabolites, daidzin-4',7-diglucoside, genistein-4'-glucoside, D-7-M, dadzein-4',7-dimethyl ether, genistein-4'-methyl ether, and genistein-7-methyl ether were detected in rats for the first time and not reported in humans. The metabolic pathways of daidzein, daidzin genistein, and genistin in rats were postulated. The biological effects of these metabolites are worthy of further investigation.

An integrated approach for studying the metabolic profiling of herbal medicine in mice using high-resolution mass spectrometry and metabolomics data processing tools.

Analysis of exposure to traditional Chinese medicine (TCM) in vivo based on mass spectrometry is helpful for the screening of effective ingredients of TCM and the development of new drugs. The method of screening biomarkers through metabolomics technology is a nontargeted research method to explore the differential components between two sets of biological samples. By taking this advantage, this study aims to takes Forsythia suspensa, which is a TCM also known as Lian Qiao (LQ), as the research object and to study its in vivo exposure by using metabolomics technology. By comparing the significant differences between biological samples before and after administration, it could be focused on the components that were significantly upregulated, where a complete set of analysis strategies for nontargeted TCM in vivo exposure mass spectrometry was established. Furthermore, the threshold parameters for peak extraction, parameter selection during statistical data analysis, and sample concentration multiples in this method have also been optimized. More interestingly, by using the established analysis strategy, we found 393 LQ-related chemical components in mice after administration, including 102 prototypes and 291 LQ-related metabolites, and plotted their metabolic profiles in vivo. In short, this study has obtained a complete mass spectrum of LQ exposure in mice in vivo for the first time, which provides a reference for research on the active ingredients of LQ in vivo. More importantly, compared with other methods, the analysis strategy of nontargeted exposure of TCM in vivo-based mass spectrometry, constructed by using this research method, has good universality and does not require self-developed postprocessing software. It is worth mentioning that, for the identification and characterization of trace amounts of metabolites in vivo, this analysis strategy has no discrimination and has a detection capability similar to that of highly exposed components.

Dapagliflozin attenuates fat accumulation and insulin resistance in obese mice with polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS), a common endocrine disorder affecting premenopausal women, is associated with various metabolic consequences such as insulin resistance, hyperlipidemia, obesity, and type 2 diabetes mellitus (T2DM). Insulin sensitizers, such as metformin and pioglitazone, though effective, often leads to significant gastrointestinal adverse effects or weight gain, limiting its suitability for women with PCOS. There is an urgent need for safe, effective and affordable agents. Dapagliflozin, a sodium-glucose co-transporter 2 (SGLT2) inhibitor, enhances glucose elimination through urine, thereby reducing body weight and improving glucose and lipid metabolism. Nevertheless, it is not currently recommended as a therapeutic option for PCOS in clinical guidelines. In this study, we systematically examined the impact of dapagliflozin on an obese PCOS mouse model, focusing on alterations in glucose metabolism, adipose tissue morphology, and plasma lipid profile. Obese PCOS was induced in mice by continuous dihydrotestosterone (DHEA) injections over 21 days and high-fat diet (HFD) feeding. PCOS mice were then orally gavaged with dapagliflozin (1 mg/kg), metformin (50 mg/kg), or vehicle daily for 8 weeks, respectively. Our results demonstrated that dapagliflozin significantly prevented body weight gain and reduced fat mass in obese PCOS mice. Meanwhile, dapagliflozin treatment improved glucose tolerance and increased insulin sensitivity compared to the control PCOS mice. Furthermore, dapagliflozin significantly improved adipocyte accumulation and morphology in white adipose tissue, resulting in a normalized plasma lipid profile in PCOS mice. In conclusion, our results suggest that dapagliflozin is an effective agent in managing glucose and lipid metabolism disorders in obese PCOS mice.

Glycyrrhetinic acid blocks SARS-CoV-2 infection by activating the cGAS-STING signalling pathway.

BACKGROUND AND PURPOSE: Traditional Chinese medicine (TCM) played an important role in controlling the COVID-19 pandemic, but the scientific basis and its active ingredients are still weakly studied. This study aims to decipher the underlying anti-SARS-CoV-2 mechanisms of glycyrrhetinic acid (GA). EXPERIMENTAL APPROACH: GA's anti-SARS-CoV-2 effect was verified both in vitro and in vivo. Homogeneous time-resolved fluorescence assays, biolayer interferometry technology, and molecular docking were employed to examine interactions of GA with human stimulator of interferon genes (hSTING). Immunofluorescence staining, western blot, and RT-qPCR were used to investigate nuclear translocation of interferon regulatory factor 3 (IRF3) and levels of STING target genes. Pharmacokinetics of GA was studied in mice. KEY RESULTS: GA could directly bind to Ser162 and Tyr240 residues of hSTING, thus up-regulating downstream targets and activation of the STING signalling pathway. Such activation is crucial for limiting the replication of SARS-CoV-2 Omicron in Calu-3 cells and protecting against lung injury induced by SARS-CoV-2 Omicron infection in K18-ACE2 transgenic mice. Immunofluorescence staining and western blot indicated that GA increased levels of phosphorylated STING, phosphorylated TANK-binding kinase-1, and cyclic GMP-AMP synthase (cGAS). Importantly, GA increased nuclear translocation of IRF3. Pharmacokinetic analysis of GA in mice indicated it can be absorbed into circulation and detected in the lung at a stable level. CONCLUSION AND IMPLICATIONS: Activation of the cGAS-STING pathway through the GA-STING-IRF3 axis is essential for the antiviral activity of GA in mice, providing new insights into the potential translation of GA for treating SARS-CoV-2 in patients.

Combined activation of artificial and natural ion channels for disrupting mitochondrial ion homeostasis towards effective postoperative tumor recurrence and metastasis suppression.

Rationale: Pharmacological targeting of mitochondrial ion channels is developing as a new direction in cancer therapy. The opening or closing of these channels can impact mitochondrial function and structure by interfering with intracellular ion homeostasis, thereby regulating cell fate. Nevertheless, their abnormal expression or regulation poses challenges in eliminating cancer cells, and further contributes to metastasis, recurrence, and drug resistance. Methods: We developed an engineered mitochondrial targeted delivery system with self-reinforcing potassium ion (K+) influx via amphiphilic mitochondrial targeting polymer (TMP) as carriers to co-deliver natural K+ channel agonists (Dinitrogen oxide, DZX) and artificial K+ channel molecules (5F8). Results: Using this method, DZX specifically activated natural K+ channels, whereas 5F8 assembled artificial K+ channels on the mitochondrial membrane, leading to mitochondrial K+ influx, as well as oxidative stress and activation of the mitochondrial apoptotic pathway. Conclusion: The synergistic effect of 5F8 and DZX presents greater effectiveness in killing cancer cells than DZX alone, and effectively inhibited tumor recurrence and lung metastasis following surgical resection of breast cancer tumors in animal models. This strategy innovatively integrates antihypertensive drugs with artificial ion channel molecules for the first time to effectively inhibit tumor recurrence and metastasis by disrupting intracellular ion homeostasis, which will provide a novel perspective for postoperative tumor therapy.