Investigation of the mechanism of nephrotoxicity of nux-vomica by PTGS2/CYP2C9-mediated arachidonic acid pathway and Jian Pi Tong Luo compound's protective effect

The clinical effectiveness of nux-vomica in treating rheumatism and arthralgia is noteworthy; however, its nephrotoxicity has sparked global concerns. Hence, there is value in conducting studies on detoxification methods based on traditional Chinese medicine compatibility theory. Blood biochemistry, enzyme-linked immunosorbent assay, and pathological sections were used to evaluate both the nephrotoxicity of nux-vomica and the efficacy of the Jian Pi Tong Luo (JPTL) compound in mitigating this toxicity. Kidney metabolomics, using ultra-high-performance liquid chromatography-quadrupole-time-of-flight-MS (UPLC-Q-TOF-MS), was applied to elucidate the alterations in small-molecule metabolites in vivo. In addition, network pharmacology analysis was used to verify the mechanism and pathways underlying the nephrotoxicity associated with nux-vomica. Finally, essential targets were validated through molecular docking and western blotting. The findings indicated significant nephrotoxicity associated with nux-vomica, while the JPTL compound demonstrated the ability to alleviate this toxicity. The mechanism potentially involves nux-vomica activating the "PTGS2/CYP2C9-phosphatidylcholine-arachidonic acid metabolic pathway." This study establishes a scientific foundation for the clinical use of nux-vomica and lays groundwork for further research and safety assessment of toxic Chinese herbal medicines.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Ceramide/Sphingosine 1-Phosphate Axis as a Key Target for Diagnosis and Treatment in Alzheimer's Disease and Other Neurodegenerative Diseases

Alzheimer's disease (AD) is considered the most prevalent neurodegenerative disease and the leading cause of dementia worldwide. Sphingolipids, such as ceramide or sphingosine 1-phosphate, are bioactive molecules implicated in structural and signaling functions. Metabolic dysfunction in the highly conserved pathways to produce sphingolipids may lead to or be a consequence of an underlying disease. Recent studies on transcriptomics and sphingolipidomics have observed alterations in sphingolipid metabolism of both enzymes and metabolites involved in their synthesis in several neurodegenerative diseases, including AD. In this review, we highlight the most relevant findings related to ceramide and neurodegeneration, with a special focus on AD.

An Integrated Metabolomic Screening Platform Discovers the Potential Biomarkers of Ischemic Stroke and Reveals the Protective Effect and Mechanism of Folic Acid

Folic acid has a protective effect against ischemic stroke. However, the protective pharmacological mechanism remains unclear. The aim of this study is to explore the protective effect of folic acid on ischemic stroke animals by an integrated metabolomic biomarker screening platform. Based on ultra-performance liquid chromatography-tandem mass spectrometry (UPLC/MS) coupled with multivariate data analysis, the changes in metabolites and pathways were characterized. We found that the metabolic alteration involved a total of 37 metabolites, of which 26 biomarkers such as γ-aminobutyric acid, lysine, glutamate, ribose, and valine can be regulated by folic acid via metabolic pathways of amino acid metabolism, carbohydrate metabolism, fatty acid metabolism, citrate cycle, and pyruvate metabolism, which may be the potential therapeutic targets of folic acid against ischemic stroke. Folic acid as an emerging potential natural anti-fibrosis agent has significant activity in protecting against middle cerebral artery occlusion-induced rat ischemic stroke model by delaying pathological development, reversing the metabolic biomarkers, and mainly regulating the perturbation in amino acid metabolism, carbohydrate metabolism, fatty acid metabolism, citrate cycle, and pyruvate metabolism. It also showed that the integrated metabolic biomarker screening platform could provide a better understanding of the therapeutic effect and mechanism of drugs.

Chinmedomics Strategy for Elucidating the Pharmacological Effects and Discovering Bioactive Compounds From Keluoxin Against Diabetic Retinopathy

Keluoxin (KLX) is an active agent in the treatment of diabetic retinopathy (DR). However, its mechanism, targets, and effective constituents against DR are still unclear, which seriously restricts its clinical application. Chinmedomics has the promise of explaining the pharmacological effects of herbal medicines and investigating the effective mechanisms. The research results from electroretinography and electron microscope showed that KLX could reduce retinal dysfunction and pathological changes by the DR mouse model. Based on effectiveness, we discovered 64 blood biomarkers of DR by nontargeted metabolomics analysis, 51 of which returned to average levels after KLX treatment including leukotriene D4 and A4, l-tryptophan, 6-hydroxymelatonin, l-phenylalanine, l-tyrosine, and gamma-linolenic acid (GLA). The metabolic pathways involved were phenylalanine metabolism, steroid hormone biosynthesis, sphingolipid metabolism, etc. Adenosine monophosphate-activated protein kinase (AMPK), extracellular signal-regulated protein kinase1/2 (ERK1/2), phosphatidylinositol-3-kinase (PI3K), and protein 70 S6 kinase (p70 S6K) might be potential targets of KLX against DR. This was related to the mammalian target of rapamycin (mTOR) signaling and AMPK signaling pathways. We applied the chinmedomics strategy, integrating serum pharm-chemistry of traditional Chinese medicine (TCM) with metabolomics, to discover astragaloside IV (AS-IV), emodin, rhein, chrysophanol, and other compounds, which were the core effective constituents of KLX when against DR. Our study was the first to apply the chinmedomics strategy to discover the effective constituents of KLX in the treatment of DR, which fills the gap of unclear effective constituents of KLX. In the next step, the research of effective constituents can be used to optimize prescription preparation, improve the quality standard, and develop an innovative drug.

Therapeutic Effect and Mechanism of Si-Miao-Yong-An-Tang on Thromboangiitis Obliterans Based on the Urine Metabolomics Approach

Si-Miao-Yong-An-Tang (SMYAT) is a classic prescription for the treatment of thromboangiitis obliterans (TAO). However, the effect and mechanism are still unclear. This experiment aims to evaluate the therapeutic effect and mechanism of SMYAT on sodium laurate solution induced thromboangiitis obliterans model rats using urine metabolomics. The therapeutic effect of SMYAT was evaluated by histopathology, hemorheology and other indexes. The urine metabolomic method, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used for clustering group and discriminant analysis to screen urine differential metabolic biomarkers, and explore new insight into pathophysiological mechanisms of SMYAT in the treatment of TAO. SMYAT has significant antithrombotic and anti-inflammatory effects, according to the results of urine metabolomic analysis, and regulate the metabolic profile of TAO rats, and its return profile is close to the state of control group. Through metabolomics technology, a total of 35 urine biomarkers of TAO model were characterized. Among them, SMYAT treatment can regulate 22 core biomarkers, such as normetanephrine and 4-pyridoxic acid. It is found that the therapeutic effect of SMYAT is closely related to the tyrosine metabolism, vitamin B6 metabolism and cysteine and methionine metabolism. It preliminarily explored the therapeutic mechanism of SMYAT, and provided a scientific basis for the application of SMYAT.

Alterations in the Gut Microbiota and Their Metabolites in Colorectal Cancer: Recent Progress and Future Prospects

Colorectal cancer (CRC) is a leading cause of cancer morbidity and mortality worldwide. The etiology and pathogenesis of CRC remain unclear. A growing body of evidence suggests dysbiosis of gut bacteria can contribute to the occurrence and development of CRC by generating harmful metabolites and changing host physiological processes. Metabolomics, a systems biology method, will systematically study the changes in metabolites in the physiological processes of the body, eventually playing a significant role in the detection of metabolic biomarkers and improving disease diagnosis and treatment. Metabolomics, in particular, has been highly beneficial in tracking microbially derived metabolites, which has substantially advanced our comprehension of host-microbiota metabolic interactions in CRC. This paper has briefly compiled recent research progress of the alterations of intestinal flora and its metabolites associated with CRC and the application of association analysis of metabolomics and gut microbiome in the diagnosis, prevention, and treatment of CRC; furthermore, we discuss the prospects for the problems and development direction of this association analysis in the study of CRC. Gut microbiota and their metabolites influence the progression and causation of CRC, and the association analysis of metabolomics and gut microbiome will provide novel strategies for the prevention, diagnosis, and therapy of CRC.

High-Throughput and Untargeted Metabolic Profiling Revealed the Potential Effect and Mechanisms of Paeoniflorin in Young Asthmatic Rats

Paeoniflorin (PF) is a multi-target monoterpenoid glycoside and possesses broad pharmacological functions, e.g., anti-inflammation, anti-depression, antitumor, abirritation, neuroprotection, antioxidant, and enhancing cognitive and learning ability. PF has gained a large amount of attention for its effect on asthma disease as the growth rate of asthma has increased in recent years. However, its mechanism of action on asthma is still unclear. In this study, we have explored the action mechanism of PF on asthma disease. Furthermore, high-throughput untargeted metabolic profiling was performed through ultraperformance liquid chromatography/electrospray ionization quadruple time-of-flight high-definition mass spectrometry (QA) UPLC-Q/TOF-MS combined with pattern recognition approaches and pathway analysis. A total of 20 potential biomarkers were discovered by UPLC/MS and urine metabolic profiling. The key pathways including the citrate cycle (the TCA cycle), pyrimidine metabolism, pentose phosphate pathway, tyrosine metabolism, and tryptophan metabolism were affected by PF. In conclusion, we have discovered metabolite biomarkers and revealed the therapeutic mechanism of PF based on liquid chromatography coupled with mass spectrometry untargeted metabolomics. The untargeted metabolomics combined with UPLC-MS is a useful tool for exploring the therapeutic mechanism and targets of PF in the treatment of asthma. Metabolomics combined with UPLC-MS is an integrated method to explore the metabolic mechanism of PF in the treatment of asthma rats and to reveal the potential targets, providing theoretical support for the study of the treatment of PF.

Liquid Chromatograph-Mass Spectrometry-Based Non-targeted Metabolomics Discovery of Potential Endogenous Biomarkers Associated With Prostatitis Rats to Reveal the Effects of Magnoflorine

Magnoflorine (Mag) has multiple pharmacological activities for the prevention and treatment of prostatitis. However, its molecular mechanisms andpharmacological targets are not clear. In this study, the ultra-performance liquid tandem mass spectrometry-based metabolomics method was used to clarify the intervention of Mag against prostatitis and the biological mechanism. A total of 25 biomarkers associated with the prostatitis model were identified by metabolomics, and a number of metabolic pathways closely related to the model were obtained by MetPA analysis. After given Mag treatment, the results of each indicator were shown that Mag alkaloid could inhibit the development of prostatitis effectively. We found that Mag had regulative effects on potential biomarkers of prostatitis model, which can regulate them to the control group. Our results indicated that alkaloids have an effective intervention therapy for prostatitis, and five types of metabolic pathways closely related to prostatitis model were obtained, including phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, tyrosine metabolism, arginine and proline metabolism, glycine, serine and threonine metabolism, alanine, aspartate and glutamate metabolism. This study has provided the basic experimental data for the development of Mag in the prevention and treatment of prostatitis.

Food and Microbiota Metabolites Associate with Cognitive Decline in Older Subjects: A 12-Year Prospective Study

SCOPE

Diet is considered an important modulator of cognitive decline and dementia, but the available evidence is, however, still fragmented and often inconsistent.

METHODS AND RESULTS

The article studies the long-term prospective Three-City Cohort, which consists of two separate nested case-control sample sets from different geographic regions (Bordeaux, n = 418; Dijon, n = 424). Cognitive decline is evaluated through five neuropsychological tests (Mini-Mental State Examination, Benton Visual Retention Test, Isaac's Set Test, Trail-Making Test part A, and Trail-Making Test part B). The food-related and microbiota-derived circulating metabolome is studied in participants free of dementia at baseline, by subjecting serum samples to large-scale quantitative metabolomics analysis. A protective association is found between metabolites derived from cocoa, coffee, mushrooms, red wine, the microbial metabolism of polyphenol-rich foods, and cognitive decline, as well as a negative association with metabolites related to unhealthy dietary components, such as artificial sweeteners and alcohol.

CONCLUSION

These results provide insight into the early metabolic events that are associated with the later risk to develop cognitive decline within the crosstalk between diet, gut microbiota and the endogenous metabolism, which can help identify potential targets for preventive and therapeutic strategies to preserve cognitive health.

High-throughput metabolomics using UPLC/Q-TOF-MS coupled with multivariate data analysis reveals the effect and mechanism of syringin against ovariectomized osteoporosis

Osteoporosis is an increasing public health problem in the worldwide and has caused socioeconomic burden. Natural products as candidates have the potential to promote bone formation and suppress bone resorption for osteoporosis treatment. Previously, syringin has showed the potent anti-osteoporosis activity, however the detailed mechanism of syringin against osteoporosis is still unclear. This study aimed to reveal the pharmacological effect and mechanism of syringin through the high-throughput metabolomics. In this study, metabolomics techniques were used to explore the metabolic biomarkers and profiles provides deep insights into the pharmacological effects and mechanism of syringin against osteoporosis. The metabolite biomarkers were monitored based on the high-resolution mass spectrometry. By the integration analysis of metabolomics technology, a total of 23 metabolic biomarkers were discovered and we found the highly relevant pathway involved in glycine and serine metabolism, butyrate metabolism, methionine metabolism, catecholamine biosynthesis, tyrosine metabolism, etc. Interestingly, synthesis and degradation of ketone bodies, phenylalanine, tyrosine and tryptophan biosynthesis, arachidonic acid metabolism, tyrosine metabolism, glycine, serine and threonine metabolism, butanoate metabolism, was related with efficacy of syringin. The present work showed that the metabolomics technology can provide novel strategies for revealing insights into the metabolic effects and action mechanism of drug.

An elaborative NMR based plasma metabolomics study revealed metabolic derangements in patients with mild cognitive impairment: a study on north Indian population

Mild cognitive impairment (MCI) is transition phase between cognitive decline and dementia. The current study aims to investigate altered metabolic pattern in plasma of MCI for potential biomarkers. MCI (N = 50) and healthy controls (HC, N = 50) age group 55-75 years were screened based on Mini Mental State Examination Test (MMSE) and diffusion tensor imaging (DTI imaging). The MMSE score of MCI was significantly lower (25.74 ± 1.83) compared to healthy control subjects (29 ± 1). The MCI patients exhibit significant changes in white matter integrity in the right frontal lobe, right temporal lobe, left frontal lobe, forcep major, fornix, corpus callosum. Further, the plasma samples of twenty seven MCI patients (N = 27) and twenty HC subjects (N = 20; having no significant differences in any demographics) were analyzed using 1H NMR based metabolomics approach. Consistent with many previous reports, the levels of several plasma metabolites were found to be elevated in MCI patients compared to healthy controls. Further univariate and multivariate ROC curve analyses provided three plasma metabolites as a diagnostic panel of biomarker for MCI; which are lysine, glycine, and glutamine. Overall, the results of this study will help to improve the diagnostic and prognostic strategies of MCI in addition to improving our understanding about disease pathogenesis. We believe that the over-nutritional metabolic phenotype of MCI needs to be targeted for developing future dietary interventions so that the progression of MCI can be limited. Metabolic derangements associated with Mild Cognitive Impairment.

Andrographolide Against Lung Cancer-New Pharmacological Insights Based on High-Throughput Metabolomics Analysis Combined with Network Pharmacology

Andrographolide (Andro) has known to treat various illnesses such as colds, diarrhea, fever and infectious diseases. However, the effect mechanism of Andro is still unclear. Therefore, we used high-throughput metabolomics analysis to discover biomarkers, metabolic profiles and pathways to reveal the pharmacological action and effective mechanism of Andro against lung cancer. The metabolic effects of Andro on lung cancer animal was explored by ultra-performance liquid chromatography-triple-time of flight/mass spectrometry (UPLC-TOF/MS) analysis. Our results showed that Andro exhibited significant protective effects against lung cancer. Compared with control group, a total of 25 metabolites biomarkers was identified in urine of model animals, which 18 of them were regulated toward the normal direction after Andro treatment, and network pharmacology analysis showed that they were related with 570 proteins. Biological pathways analysis showed that the 11 metabolism pathways were regulated by Andro treatment in lung cancer mouse, and amino acid metabolism and arachidonic acid metabolism have great potential as target pathways for Andro against lung cancer. It revealed that high-throughput metabolomics combined with network pharmacology analysis provides deeply insight into the therapeutic mechanisms of natural product for promoting medicine development and disease treatment.

Cyclodextrin dimers: A versatile approach to optimizing encapsulation and their application to therapeutic extraction of toxic oxysterols

We have developed a novel class of specifically engineered, dimerized cyclodextrin (CD) nanostructures for the encapsulation of toxic biomolecules such as 7-ketocholesterol (7KC). 7KC accumulates over time and causes dysfunction in many cell types, linking it to several age-related diseases including atherosclerosis and age-related macular degeneration (AMD). Presently, treatments for these diseases are invasive, expensive, and show limited benefits. CDs are cyclic glucose oligomers utilized to capture small, hydrophobic molecules. Here, a combination of in silico, in vitro, and ex vivo methods is used to implement a synergistic rational drug design strategy for developing CDs to remove atherogenic 7KC from cells and tissues. Mechanisms by which CDs encapsulate sterols are discussed, and we conclude that covalently linked head-to-head dimers of βCDs have substantially improved affinity for 7KC compared to monomers. We find that inclusion complexes can be stabilized or destabilized in ways that allow the design of CD dimers with increased 7KC selectivity while maintaining an excellent safety profile. These CD dimers are being developed as therapeutics to treat atherosclerosis and other debilitating diseases of aging.

Identification of key lipid metabolites during metabolic dysregulation in the diabetic retinopathy disease mouse model and efficacy of Keluoxin capsule using an UHPLC-MS-based non-targeted lipidomics approach

Diabetic retinopathy (DR) is an important complication of diabetes, and is currently the main cause of blindness among young adults in the world. Previous studies have shown that Keluoxin (KLX) capsules have a significant effect on DR in C57BL/KsJ/db-/- mice (db/db mice), however the unclear mechanism limits its further clinical application and actual value. Further research is urgently needed for the treatment of DR disease. Discovery of key lipid biomarkers and metabolic pathways can reveal and explore the molecular mechanisms related to DR development and discover the effect of Keluoxin (KLX) capsule against DR in db/db mice. Lipidomics has been used for characterizing the pathological conditions via identification of key lipid metabolites and the metabolic pathway. In this study, the high-throughput lipidomics using UHPLC-Q-TOF/MS combined with multivariate statistical analysis, querying multiple network databases and employing ingenuity pathway analysis (IPA) method for molecular target prediction. A total of 30 lipid biomarkers were identified and 7 metabolic pathways including arachidonic acid metabolism and steroid hormone biosynthesis were found. The preventive effect of KLX intervention can regulate 22 biomarkers such as LysoPA(16:0/0:0), prostaglandin D2, cortisol and γ-linolenic acid, etc. IPA platform has predicted that PI3K/MAPK pathway are closely related to DR development. It also showed that high-throughput lipidomics combined with multivariate statistical analysis could deep excavate of the biological significance of the big data, and can provide molecular targets information about the disease treatment.

High-throughput metabolomics discovers metabolite biomarkers and insights the protective mechanism of schisandrin B on myocardial injury rats

Schisandrin B has been proved to possess anti-inflammatory and anti-endoplasmic effects, could improve cardiac function, inhibit apoptosis, and reduce inflammation after ischemic injury. However, the detailed metabolic mechanism and potential pathways of Schisandrin B effects on myocardial injury are unclear. Metabolomics could yield in-depth mechanistic insights and explore the potential therapeutic effect of natural products. In this study, the preparation of doxorubicin-induced myocardial injury rat model for evaluation of Schisandrin B on viral myocarditis sequelae related pathological changes and its mechanism. The metabolite profiling of myocardial injury rats was performed through ultra-high performance liquid chromatography combined with mass spectrometry combined with pattern recognition approaches and pathway analysis. A total of 15 metabolites (nine in positive ion mode and six in negative ion mode) were considered as potential biomarkers of myocardial injury, and these metabolites may correlate with the regulation of Schisandrin B treatment. A total of six metabolic pathways are closely related to Schisandrin B treatment, including glycerophospholipid metabolism, sphingolipid metabolism, purine metabolism, etc. This study revealed the potential biomarkers and metabolic network pathways of myocardial injury, and illuminated the protective mechanism of Schisandrin B on myocardial injury.

High-throughput metabolomics method based on liquid chromatography-mass spectrometry: Insights into the underlying mechanisms of salinity-alkalinity exposure-induced metabolites changes in Barbus capito

It is critical to investigate the adaptive development and the physiological mechanism of fish in external stimulation. In this study, the response of Barbus capito to salinity-alkalinity exposure was explored by high-throughput nontargeted and liquid chromatography-mass spectrometry-based metabolomics to investigate metabolic biomarker and pathway changes. Meanwhile, the biochemical indexes of Barbus capito were measured to discover the chronic impairment response to salinity-alkalinity exposures. A total of 29 tissue metabolites were determined to deciphering the endogenous metabolic changes of fishes during the different concentration salinity-alkalinity exposures environment, which were mainly involved in the key metabolism including the phenylalanine, tyrosine, and tryptophan biosynthesis, arachidonic acid metabolism, pyruvate metabolism, citrate cycle, and glycerophospholipid metabolism. Finally, we found the amino acid metabolism as key target was associated with the endogenous metabolites and metabolic pathways of Barbus capito to salinity-alkalinity exposures. In conclusion, metabolomics is a potentially powerful tool to reveal the mechanism information of fish in various exposure environments.

Functional Metabolomics Analysis Elucidating the Metabolic Biomarker and Key Pathway Change Associated With the Chronic Glomerulonephritis and Revealing Action Mechanism of Rhein

Chronic glomerulonephritis (CGN) as the culprit of kidney failure can increase the mortality of critically ill patients and seriously threatens people’s health all over the world. This study using metabolomics strategy is to reveal the potential therapeutic mechanism-related targets to evaluate the effects of rhein (RH) on CGN rats. Changes of serum metabolites and pathways were analyzed by non-targeted metabolomic method based on liquid chromatography-mass spectrometry (LC-MS) combined with ingenuity pathway analysis. In addition, the levels of biochemical indicators were also detected. A total of 25 potential biomarkers were identified to express serum metabolic turbulence in CGN animal model, and then 16 biomarkers were regulated by RH trending to the normal states. From metabolite enrichment and pathway analysis, pharmacological activity of RH on CGN were mainly involved in six vital metabolic pathways including phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, tricarboxylic acid cycle (TCA cycle), alanine, aspartate, and glutamate metabolism, arginine and proline metabolism. It suggested CGN treatment with RH, which may be mediated via interference with metabolic pathway such as amino acid metabolism, arachidonic acid metabolism, and TCA cycle to regulating inflammation, oxidation response and immune regulation against CGN. It showed that metabolomics method offer deeply insight into the therapeutic mechanisms of natural product.

Network pharmacology combined with metabolomics approach to investigate the protective role and detoxification mechanism of Yunnan Baiyao formulation

BACKGROUND

Yunnan Baiyao (YNBY) is a traditional Chinese medicine formulae, which has the functions of hemostasis, activating blood circulation and removing blood stasis, anti-inflammation, etc. Although the presence of Caowu (CW, Aconiti Kusnezoffii Radix), the detoxification mechanism of YNBY is still unclear.

PURPOSE

In current study, network pharmacology, toxicological methods and metabolomics technique were applied to explore YNBY in attenuating toxicity of CW.

METHODS

Prediction of targets and pathways of CW were carried out by commonly used network pharmacological method. Simultaneously, SD rats were orally administrated with CW, processed CW (ZCW), YNBY, and YNBY which lack of CW (QCW) for 15 days. Tissue samples were observed with histopathology. Urine samples were analyzed with ultra-performance liquid chromatography-mass spectrometry to screen differential metabolites and related metabolic pathways associated with toxicity of CW. Furthermore, by comparing the changes of the metabolite contents, focused the attenuated metabolic pathway. Finally, the network pharmacological and experimental data were integrated to investigate detoxification mechanism of YNBY.

RESULTS

A total of 44 potential toxicity biomarkers were identified and 14 related pathways were involved in the toxicity of CW. Furthermore, 5 core toxicity biomarkers (2-keto-6-acetamidocaproate, γ-glutamylleucine, prostaglandin E₃, 4-hydroxy-5-(3'-hydroxyphenyl)-valeric acid-3'-O-sulphate, and 3,4-dihydroxy- phenylglycol O-sulfate) were regulated to normal condition in YNBY group. Lysine degradation was locked as the core metabolic pathway of detoxification of YNBY. Integrating the predicted results of network pharmacology, ACHE, SLC6A3, SLC6A4 might be the target of protective role of other herbs in YNBY.

CONCLUSION

Network pharmacology combined with metabolomics exhibited a powerful mean to investigate the herbal toxicity and probed into the detoxification mechanism of formulae, which contributes to its safety evaluation.

High-Throughput Metabolomics Method for Discovering Metabolic Biomarkers and Pathways to Reveal Effects and Molecular Mechanism of Ethanol Extract From Epimedium Against Osteoporosis

Metabolomics is an effective strategy to explore the molecular mechanism of herbal medicine. Epimedium, a traditional Chinese herb from the Epimedium brevicornu Maxim., has a therapeutic effect on osteoporosis (OP), however the molecular mechanism of the anti-OP effect is uncle\ar. Therefore, we investigated the pharmacological effect and action mechanism of ethanol extract of epimedium (Ext-epi) onOP rat model. The serum of OP rats was analyzed utilized UPLC-Q-TOF/MS metabolomics, and the potential biomarkers were screened and identified using multivariate data analysis systems and network databases. To further appraise the influence of Ext-epi on biological markers and metabolic pathways, and reveal the potential mechanism of Ext-epi on OP treatment. The results showed that 46 potential biomarkers were screened out and after intervention with Ext-epi extracts solution, 16 potential biomarkers were significantly recalled. Further pathway experiments showed that key pathway analysis include sarachidonic acid metabolism, glycerolphospholipid metabolism as potential targets which is related with the efficacy of Ext-epi protect against OP. These results explain the correlation between metabolites and molecular mechanisms, which is of great significance for understanding the intervention of Ext-epi on OP. In short, based on UPLC-Q-TOF/MS metabolomics may provide effective strategies for understanding the pathogenesis of diseases and evaluating the intervention effect of natural products.

UPLC-MS metabolomics method provides valuable insights into the effect and underlying mechanisms of Rhizoma Drynariae protecting osteoporosis

Osteoporosis (OP) is a metabolic bone disease in which that volume of bone tissue per unit volume decrease, which is a common disease disturbing the elderly or postmenopausal women. Rhizoma Drynariae (RD) is a kind of herb widely used in thousands of years of clinical practice in China to tonify kidney and prevent osteoporosis, with reliable curative effect. However, the mechanism of its anti-osteoporosis action is still unclear. This study is dedicated to exploration the therapeutic effect of RD on retinoic acid solution-induced OP model rats based on high-throughput metabolomics technology platform, and reveal its influence on metabolomics level, so as to find effective potential biomarkers and therapeutic targets for diagnosing OP. OP model was established by intragastric administration of retinoic acid solution for 21 days, and then the treatment group was treated by intragastric administration of RD solution for 60 days. Blood samples of all groups were collected and analyzed based on UPLC-MS metabolomics and combined with EZinfo 3.0 data analysis, 32 potential biomarkers were identified, including 22 in ESI+ and 10 in ESI-, these biomarkers are related to 9 metabolic pathways. After treatment with RD solution, 21 biomarkers were obviously regulated, these mainly affected linoleic acid metabolic, glycerophospholipid metabolism and arachidonic acid metabolism pathway. The results show that RD can reduce the risk of OP disease, which may be related to the metabolic pathway mentioned above, and provides the foundation for the administer prophylaxis and treatment of OP with natural products.

A multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap

Aetiological and clinical heterogeneity is increasingly recognized as a common characteristic of Alzheimer's disease and related dementias. This heterogeneity complicates diagnosis, treatment, and the design and testing of new drugs. An important line of research is discovery of multimodal biomarkers that will facilitate the targeting of subpopulations with homogeneous pathophysiological signatures. High-throughput 'omics' are unbiased data-driven techniques that probe the complex aetiology of Alzheimer's disease from multiple levels (e.g. network, cellular, and molecular) and thereby account for pathophysiological heterogeneity in clinical populations. This review focuses on data reduction analyses that identify complementary disease-relevant perturbations for three omics techniques: neuroimaging-based subtypes, metabolomics-derived metabolite panels, and genomics-related polygenic risk scores. Neuroimaging can track accrued neurodegeneration and other sources of network impairments, metabolomics provides a global small-molecule snapshot that is sensitive to ongoing pathological processes, and genomics characterizes relatively invariant genetic risk factors representing key pathways associated with Alzheimer's disease. Following this focused review, we present a roadmap for assembling these multiomics measurements into a diagnostic tool highly predictive of individual clinical trajectories, to further the goal of personalized medicine in Alzheimer's disease.

Insulin resistance and impaired lipid metabolism as a potential link between diabetes and Alzheimer's disease

Diabetes disrupts organs throughout the body including the brain. Evidence suggests diabetes is a risk factor for Alzheimer's disease (AD) and neurodegeneration. In this review, we focus on understanding how diabetes contributes to the progression of neurodegeneration by influencing several aspects of the disease process. We emphasize the potential roles of brain insulin resistance, as well as cholesterol and lipid disruption, as factors which worsen AD.

Exploring the metabolic biomarkers and pathway changes in crucian under carbonate alkalinity exposure using high-throughput metabolomics analysis based on UPLC-ESI-QTOF-MS

The aims of this study is to explore the metabolomic biomarker and pathway changes in crucian under carbonate alkalinity exposures using high-throughput metabolomics analysis based on ultra-performance liquid chromatography-electrospray ionization-quadrupole time of flight-tandem mass spectrometry (UPLC-ESI-QTOF-MS) for carrying out adaptive evolution of fish in environmental exposures and understanding molecular physiological mechanisms of saline–alkali tolerance in fishes. Under 60 day exposure management, the UPLC-ESI-QTOF-MS technology, coupled with a pattern recognition approach and metabolic pathway analysis, was utilized to give insight into the metabolic biomarker and pathway changes. In addition, biochemical parameters in response to carbonate alkalinity in fish were detected for chronic impairment evaluation. A total of twenty-seven endogenous metabolites were identified to distinguish the biochemical changes in fish in clean water under exposure to different concentrations of carbonate alkalinity (CA); these mainly involved amino acid synthesis and metabolism, arachidonic acid metabolism, glyoxylate and dicarboxylate metabolism, pyruvate metabolism and the citrate cycle (TCA cycle). Compared with the control group, CA exposure increased the level of blood ammonia; TP; ALB; Gln in the liver and gills; GS; urea in blood, the liver and gills; CREA; CPS; Glu and LDH; and decreased the level of weight gain rate, oxygen consumption, discharge rate of ammonia, SOD, CAT, ALT, AST and Na⁺/K⁺-ATPase. At low concentrations, CA can change the normal metabolism of fish in terms of changing the osmotic pressure regulation capacity, antioxidant capacity, ammonia metabolism and liver and kidney function to adapt to the CA exposure environment. As the concentration of CA increases, various metabolic processes in crucian are inhibited, causing chronic damage to the body. The results show that the metabolomic strategy is a potentially powerful tool for identifying the mechanisms in response to different environmental exposomes and offers precious information about the chronic response of fish to CA.

We explore the metabolic biomarker and pathway changes accompanying the adaptive evolution of crucian subjected to carbonate alkalinity exposure, using UPLC-ESI-QTOF-MS, in order to understand the molecular physiological mechanisms of saline–alkali tolerance.

Oxidized cholesterol species as signaling molecules in the brain: diabetes and Alzheimer's disease

Type 2 diabetes is associated with adverse central nervous system effects, including a doubled risk for Alzheimer's disease (AD) and increased risk of cognitive impairment, but the mechanisms connecting diabetes to cognitive decline and dementia are unknown. One possible link between these diseases may be the associated alterations to cholesterol oxidation and metabolism in the brain. We will survey evidence demonstrating alterations to oxysterols in the brain in AD and diabetes and how these oxysterols could contribute to pathology, as well as identifying research questions that have not yet been addressed to allow for a fuller understanding of the role of oxysterols in AD and diabetes.

Application of NMR metabolomics to search for human disease biomarkers in blood

Recently, nuclear magnetic resonance spectroscopy (NMR)-based metabolomics analysis and multivariate statistical techniques have been incorporated into a multidisciplinary approach to profile changes in small molecules associated with the onset and progression of human diseases. The purpose of these efforts is to identify unique metabolite biomarkers in a specific human disease so as to (1) accurately predict and diagnose diseases, including separating distinct disease stages; (2) provide insights into underlying pathways in the pathogenesis and progression of the malady and (3) aid in disease treatment and evaluate the efficacy of drugs. In this review we discuss recent developments in the application of NMR-based metabolomics in searching disease biomarkers in human blood samples in the last 5 years.

Rapid lipidomics analysis for sepsis-induced liver injury in rats and insights into lipid metabolic pathways using ultra-performance liquid chromatography/mass spectrometry

Lipidomics has been applied in the identification and quantification of molecular lipids within an organism, and to provide insights into mechanisms in clinical medicine. Sepsis is a major systemic inflammatory syndrome and the liver here is a potential target organ for dysfunctional response. However, the study of alterations in global lipid profiles associated with sepsis-induced liver injury is still limited. In this work, we set out to determine alterations of lipidomics profiles in a rat model of sepsis-induced liver injury using an untargeted lipidomics strategy. Liquid chromatography coupled with mass spectrometry in conjunction with multivariate data analysis and pathway analysis were used to acquire a global lipid metabolite profile. Meanwhile, biochemistry index and histopathological examinations of the liver were performed to obtain auxiliary measurements for determining the pathological changes associated with sepsis-induced liver injury. Eleven lipid metabolites and two metabolic pathways were discovered and associated with sepsis-induced liver injury. The results indicated that various biomarkers and pathways may provide evidence for and insight into lipid profile alterations associated with sepsis-induced liver injury, and hence pointed to potential strategic targets for clinical diagnosis and therapy in the future.

Lipidomics has been applied in the identification and quantification of molecular lipids within an organism, and to provide insights into mechanisms in clinical medicine.

Recent advances from metabolomics and lipidomics application in alzheimer's disease inspiring drug discovery

Introduction: Although age is a major risk factor for Alzheimer's disease (AD), it is not an inevitable consequence of aging nor is it exclusively an old-age disease. Several other major risk factors for AD are strongly associated with metabolism and include lack of exercise, obesity, diabetes, high blood pressure and cholesterol, over-consumption of alcohol and depression in addition to low educational level, social isolation, and cognitive inactivity. Approaches for Alzheimer prevention and treatment through manipulation of metabolism and utilization of active metabolites have great potential either as a primary or secondary treatment avenue or as a preventative strategy in high-risk individuals.Areas covered: This review outlines the current knowledge concerning the relationship between AD and metabolism and the novel treatments attempting to correct changes in AD patients determined through metabolomics or lipidomic analyses.Expert opinion: Metabolites are one of the main driving factors and indicators of AD and can offer many possible avenues for prevention and treatment. However, with the highly interconnected effects of metabolites and metabolism, as well as the many different routes for metabolism dysfunction, successful treatment would have to include the correction of metabolic errors as well as errors in transport and metabolite processing in order to affect and revert AD progression.

Metabolomics Analyses of Saliva Detect Novel Biomarkers of Alzheimer's Disease

Using a non-invasive biofluid (saliva), we apply a powerful metabolomics workflow for unbiased biomarker discovery in Alzheimer's disease (AD). We profile and differentiate Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and AD groups. The workflow involves differential chemical isotope labeling liquid chromatography mass spectrometry using dansylation derivatization for in-depth profiling of the amine/phenol submetabolome. The total sample (N = 109) was divided in to the Discovery Phase (DP) (n = 82; 35 CN, 25 MCI, 22 AD) and a provisional Validation Phase (VP) (n = 27; 10 CN, 10 MCI, 7 AD). In DP we detected 6,230 metabolites. Pairwise analyses confirmed biomarkers for AD versus CN (63), AD versus MCI (47), and MCI versus CN (2). We then determined the top discriminating biomarkers and diagnostic panels. A 3-metabolite panel distinguished AD from CN and MCI (DP and VP: Area Under the Curve [AUC] = 1.000). The MCI and CN groups were best discriminated with a 2-metabolite panel (DP: AUC = 0.779; VP: AUC = 0.889). In addition, using positively confirmed metabolites, we were able to distinguish AD from CN and MCI with good diagnostic performance (AUC > 0.8). Saliva is a promising biofluid for both unbiased and targeted AD biomarker discovery and mechanism detection. Given its wide availability and convenient accessibility, saliva is a biofluid that can promote diversification of global AD biomarker research.

Alteration of Sphingolipids in Biofluids: Implications for Neurodegenerative Diseases

Sphingolipids (SL) modulate several cellular processes including cell death, proliferation and autophagy. The conversion of sphingomyelin (SM) to ceramide and the balance between ceramide and sphingosine-1-phosphate (S1P), also known as the SL rheostat, have been associated with oxidative stress and neurodegeneration. Research in the last decade has focused on the possibility of targeting the SL metabolism as a therapeutic option; and SL levels in biofluids, including serum, plasma, and cerebrospinal fluid (CSF), have been measured in several neurodegenerative diseases with the aim of finding a diagnostic or prognostic marker. Previous reviews focused on results from diseases such as Alzheimer's Disease (AD), evaluated total SL or species levels in human biofluids, post-mortem tissues and/or animal models. However, a comprehensive review of SL alterations comparing results from several neurodegenerative diseases is lacking. The present work compiles data from circulating sphingolipidomic studies and attempts to elucidate a possible connection between certain SL species and neurodegeneration processes. Furthermore, the effects of ceramide species according to their acyl-chain length in cellular pathways such as apoptosis and proliferation are discussed in order to understand the impact of the level alteration in specific species. Finally, enzymatic regulations and the possible influence of insulin resistance in the level alteration of SL are evaluated.

Metabolomic Analysis Identifies Alterations of Amino Acid Metabolome Signatures in the Postmortem Brain of Alzheimer's Disease

Despite significant advances in neuroscience research over the past several decades, the exact cause of AD has not yet fully understood. The metabolic hypothesis as well as the amyloid and tau hypotheses have been proposed to be associated with AD pathogenesis. In order to identify metabolome signatures from the postmortem brains of sporadic AD patients and control subjects, we performed ultra performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometer (UPLC-LTQ-Orbitrap-MS). Not only our study identified new metabolome signatures but also verified previously known metabolome profiles in the brain. Statistical modeling of the analytical data and validation of the structural assignments discovered metabolic biomarkers associated with the AD pathogenesis. Interestingly, hypotaurin, myo-inositol and oxo-proline levels were markedly elevated in AD while lutamate and N-acetyl-aspartate were decreased in the postmortem brain tissue of AD patients. In addition, neurosteroid level such as cortisol was significantly increased in AD. Together, our data indicate that impaired amino acid metabolism is associated with AD pathogenesis and the altered amino acid signatures can be useful diagnostic biomarkers of AD. Thus, modulation of amino acid metabolism may be a possible therapeutic approach to treat AD.

Retracted Article: A high-throughput metabolomics strategy for discovering the influence of differential metabolites and metabolic pathways of huaxian capsules on sepsis-associated Qi deficiency and blood stasis syndrome

High-throughput metabolomics can be used to investigate the therapeutic targets and metabolic mechanisms of traditional Chinese medicine formulae.

Mass spectrometry is a multifaceted weapon to be used in the battle against Alzheimer's disease: Amyloid beta peptides and beyond

Amyloid-β peptide (Aβ) accumulation and aggregation have been considered for many years the main cause of Alzheimer's disease (AD), and therefore have been the principal target of investigation as well as of the proposed therapeutic approaches (Grasso [2011] Mass Spectrom Rev. 30: 347-365). However, the amyloid cascade hypothesis, which considers Aβ accumulation the only causative agent of the disease, has proven to be incomplete if not wrong. In recent years, actors such as metal ions, oxidative stress, and other cofactors have been proposed as possible co-agents or, in some cases, main causative factors of AD. In this scenario, MS investigation has proven to be fundamental to design possible diagnostic strategies of this elusive disease, as well as to understand the biomolecular mechanisms involved, in the attempt to find a possible therapeutic solution. We review the current applications of MS in the search for possible Aβ biomarkers of AD to help the diagnosis of the disease. Recent examples of the important contributions that MS has given to prove or build theories on the molecular pathways involved with such terrible disease are also reviewed.

Alzheimer's Biomarkers From Multiple Modalities Selectively Discriminate Clinical Status: Relative Importance of Salivary Metabolomics Panels, Genetic, Lifestyle, Cognitive, Functional Health and Demographic Risk Markers

Background: Among the neurodegenerative diseases of aging, sporadic Alzheimer’s disease (AD) is the most prevalent and perhaps the most feared. With virtually no success at finding pharmaceutical therapeutics for altering progressive AD after diagnosis, research attention is increasingly directed at discovering biological and other markers that detect AD risk in the long asymptomatic phase. Both early detection and precision preclinical intervention require systematic investigation of multiple modalities and combinations of AD-related biomarkers and risk factors. We extend recent unbiased metabolomics research that produced a set of metabolite biomarker panels tailored to the discrimination of cognitively normal (CN), cognitively impaired and AD patients. Specifically, we compare the prediction importance of these panels with five other sets of modifiable and non-modifiable AD risk factors (genetic, lifestyle, cognitive, functional health and bio-demographic) in three clinical groups.

Method: The three groups were: CN (n = 35), mild cognitive impairment (MCI; n = 25), and AD (n = 22). In a series of three pairwise comparisons, we used machine learning technology random forest analysis (RFA) to test relative predictive importance of up to 19 risk biomarkers from the six AD risk domains.

Results: The three RFA multimodal prediction analyses produced significant discriminating risk factors. First, discriminating AD from CN was the AD metabolite panel and two cognitive markers. Second, discriminating AD from MCI was the AD/MCI metabolite panel and two cognitive markers. Third, discriminating MCI from CN was the MCI metabolite panel and seven markers from four other risk modalities: genetic, lifestyle, cognition and functional health.

Conclusions: Salivary metabolomics biomarker panels, supplemented by other risk markers, were robust predictors of: (1) clinical differences in impairment and dementia and even; (2) subtle differences between CN and MCI. For the latter, the metabolite panel was supplemented by biomarkers that were both modifiable (e.g., functional) and non-modifiable (e.g., genetic). Comparing, integrating and identifying important multi-modal predictors may lead to novel combinations of complex risk profiles potentially indicative of neuropathological changes in asymptomatic or preclinical AD.

Retracted Article: High performance liquid chromatography coupled with high resolution mass spectrometry-based characterization of lipidomic responses from rats with kidney injuries

Metabolism of lipids is essential for the regulation of a variety of key cellular functions. Recent advances in high performance liquid chromatography coupled with high resolution mass spectrometry have expanded our knowledge of lipid metabolism in diseases. Currently, sepsis is one of the most important public health problems all over the world, which is a serious systemic inflammatory syndrome leading to infection by various agents or trauma and subsequently to a multiple organ dysfunction response. However, little is known about the lipids affected by sepsis and their roles in kidney injuries. In this study, we present targeted and non-targeted lipidomics strategies to discover the lipid metabolism variation in serum in rats with sepsis-induced kidney injuries. Liquid chromatography (LC) coupled with mass spectrometry (MS) and multivariate data analysis were used to obtain the global lipid metabolic profiles. In addition, biochemical parameters and histopathological examination results for the kidney were analyzed to support the pathological changes during sepsis-induced kidney injury. The identification of ten proposed lipids and five relevant pathways will promote a better understanding of lipid profile alterations in kidney injury. The results suggested that lipid metabolism in sepsis-induced kidney injury had changed significantly and contribute by offering potential targets for clinical diagnosis and therapy in the future, which would be worth further studies to broaden the applications of high performance liquid chromatography coupled with high resolution mass spectrometry in the study of lipid metabolism.

In this study, we present targeted and non-targeted lipidomics strategies to discover the lipid metabolism variation in serum in rats with sepsis-induced kidney injuries.

LC-MS-based plasma metabolomics reveals metabolic variations in ovariectomy-induced osteoporosis in female Wistar rats

Osteoporosis with a reduction in bone mineral density has become one of the most common metabolic bone diseases.

Metabolomic estimation of the diagnosis of hepatocellular carcinoma based on ultrahigh performance liquid chromatography coupled with time-of-flight mass spectrometry

Metabolomics has been shown to be an effective tool for biomarker screening and pathway characterization and disease diagnosis. Metabolic characteristics of hepatocellular carcinoma (HCC) may enable the discovery of novel biomarkers for its diagnosis. In this work, metabolomics was used to investigate metabolic alterations of HCC patients. Plasma samples from HCC patients and age-matched healthy controls were investigated using high resolution ultrahigh performance liquid chromatography-mass spectrometry and metabolic differences were analyzed using pattern recognition methods. 23 distinguishable metabolites were identified. The altered metabolic pathways were associated with arginine and proline metabolism, glycine, serine and threonine metabolism, steroid hormone biosynthesis, starch and sucrose metabolism, etc. To demonstrate the utility of plasma biomarkers for the diagnosis of HCC, five metabolites comprising deoxycholic acid 3-glucuronide, 6-hydroxymelatonin glucuronide, 4-methoxycinnamic acid, 11b-hydroxyprogesterone and 4-hydroxyretinoic acid were selected as candidate biomarkers. These metabolites that contributed to the combined model could significantly increase the diagnostic performance of HCC. It has proved to be a powerful tool in the discovery of new biomarkers for disease detection and suggest that panels of metabolites may be valuable to translate our findings to clinically useful diagnostic tests.

Metabolomics has been shown to be an effective tool for biomarker screening and pathway characterization and disease diagnosis.

Metabolic Biomarkers and Neurodegeneration: A Pathway Enrichment Analysis of Alzheimer's Disease, Parkinson's Disease, and Amyotrophic Lateral Sclerosis

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) lack robust diagnostics and prognostic biomarkers. Metabolomics is a postgenomics field that offers fresh insights for biomarkers of common complex as well as rare diseases. Using data on metabolite-disease associations published in the previous decade (2006-2016) in PubMed, ScienceDirect, Scopus, and Web of Science, we identified 101 metabolites as putative biomarkers for these three neurodegenerative diseases. Notably, uric acid, choline, creatine, L-glutamine, alanine, creatinine, and N-acetyl-L-aspartate were the shared metabolite signatures among the three diseases. The disease-metabolite-pathway associations pointed out the importance of membrane transport (through ATP binding cassette transporters), particularly of arginine and proline amino acids in all three neurodegenerative diseases. When disease-specific and common metabolic pathways were queried by using the pathway enrichment analyses, we found that alanine, aspartate, glutamate, and purine metabolism might act as alternative pathways to overcome inadequate glucose supply and energy crisis in neurodegeneration. These observations underscore the importance of metabolite-based biomarker research in deciphering the elusive pathophysiology of neurodegenerative diseases. Future research investments in metabolomics of complex diseases might provide new insights on AD, PD, and ALS that continue to place a significant burden on global health.

A comparative study of the main constituents and antidepressant effects of raw and vinegar-baked Bupleuri Radix in rats subjected to chronic unpredictable mild stress

Bupleuri Radix (BR) is a traditional Chinese medicine (TCM) widely used in Asian nations, which originates fromBupleurum chinenseDC orBupleurum scorzonerifoliumWilld.

Urine metabolic phenotypes analysis of extrahepatic cholangiocarcinoma disease using ultra-high performance liquid chromatography-mass spectrometry

Extrahepatic cholangiocarcinoma (ECC) is the second most common type of malignant primary tumor with a poor survival rate and an increasing global trend.

High-resolution mass spectrometry for exploring metabolic signatures of sepsis-induced acute kidney injury

Sepsis is a commonly encountered scenario in an intensive care unit (ICU), and the kidney is one of the organs frequently affected.

Urinary UPLC-MS metabolomics dissecting the underlying mechanisms of Huaxian capsule protects against sepsis

Urinary UPLC-MS metabolomics could dissect the underlying mechanisms of HXC protects against SS.

High-throughput metabolomics analysis discovers salivary biomarkers for predicting mild cognitive impairment and Alzheimer's disease

Mild cognitive impairment (MCI) confers an increased risk of developing Alzheimer's disease (AD).