Lufeng Hu

Brain metabolomics in rats after administration of ketamine

In this study, we developed a brain metabolomic method, based on gas chromatography-mass spectrometry (GC/MS), to evaluate the effect of ketamine on rats. Pattern recognition analysis, including both principal component analysis and partial least squares-discriminate analysis revealed that ketamine induced metabolic perturbations. Compared with the control group, the levels of glycerol, uridine, cholesterol in rat brain of the ketamine group (50 mg/kg, 14 days) decreased, while the urea levels increased. Our results indicate that metabolomic methods based on GC/MS may be useful to elucidate ketamine abuse through the exploration of biomarkers.

Pharmacokinetics in rats and tissue distribution in mouse of berberrubine by UPLC-MS/MS

Berberrubine is an isoquinoline alkaloid isolated from Berberis vulgaris L, and it is readily derived from berberine. In this study, a sensitive and selective ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for the determination of berberrubine in rat plasma and mouse tissue has been developed. Magnoflorine was employed as an internal standard (IS), and liquid-liquid extraction by ethyl acetate was used for sample preparation. Chromatographic separation was achieved on a UPLC BEH C18 column (2.1mm×100mm, 1.7μm) with 0.1% formic acid and acetonitrile as the mobile phase with gradient elution. An electrospray ionization source was applied and operated in positive ion mode; multiple reactions monitoring (MRM) mode was used for quantification using target fragment ions m/z 322.0→307.0 for berberrubine and m/z 342.8→298.2 for IS. Calibration plots were linear in the range of 2-2000ng/mL for berberrubine in rat plasma and mouse tissue. Mean recoveries of berberrubine in rat plasma ranged from 79.6% to 84.8%. Intra-day and inter-day precision were less than 11%. The accuracy ranged from 93.6% to 106.8%. The method has also been successfully applied in pharmacokinetics and tissue distribution study of berberrubine. The absolute bioavailability of berberrubine was determined to be 31.6%. The results also show that berberrubine is rapidly absorbed and widely distributed in various tissues. The level of berberrubine in liver is highest, and followed by kidney, spleen and heart. Furthermore, the concentration of berberrubine in various tissues could also be predicted by a BP-ANN model.

Serum metabolomics in rats models of ketamine abuse by gas chromatography–mass spectrometry

This study aims to evaluate the effect of ketamine on rats by examining the differences in serum metabolites between ketamine abuse group (Ket-group) and control group (Con-group). Compared to the Con-group, the level of phosphate, propanoic acid, ribitol and d-fructose of the Ket-group increased after continuous intraperitoneal administration of ketamine for 7 days, while the level of alanine, glycine, butanoic acid, valine, l-serine, l-proline, mannonic acid, octadecanoic acid and cholesterol decreased. After 14 days administration, the level of alanine, butanoic acid, valine, l-leucine, phosphate, l-serine, l-threonine, propanetricarboxylic acid, hexadecanoic acid and oleic acid of the ketamine group increased while the level of mannonic acid, octadecanoic acid and cholesterol decreased. After stopping ketamine administration for 2 days, the level of butanoic acid, phosphate, aminomalonic acid, gluconic acid, hexadecanoic acid, oleic acid and arachidonic acid of Ket-group increased, while the level of glycine, l-lysine and cholesterol decreased. This study can provide invaluable information for the metabolites changes due to ketamine abuse.

A gas chromatography–mass spectrometry based study on serum metabolomics in rats chronically poisoned with hydrogen sulfide

Hydrogen sulfide poisoning is a common occupational hazard, whose mortality and incidence rates are first and second, respectively, among occupational poisoning incidents in China. The main target organs of its toxicity are in the central nervous system and respiratory system. However, there are currently no specific direct tests that can be used to diagnose poisoned patients. In this study, we developed a serum metabonomic method using orthogonal partial least squares-discriminate analysis (OPLS-DA), based on gas chromatography-mass spectrometry (GC/MS) to evaluate the effect of chronic poisoning by hydrogen sulfide in rats. The OPLS-DA data demonstrated that the model group (nxa0=xa060) differed significantly from the control group (nxa0=xa030), suggesting that the metabolic profiles of the two groups are markedly different. Alterations in the levels of some metabolites such as citrate, galactose, lactate, mannose, inositol, urea, phosphate, alanine and valine were detected by OPLS-DA analysis. We observed changes in metabolic pathways including lipid metabolism, energy metabolism and amino metabolism in the model group. Our results indicate that GC/MS-based metabonomic methods may provide novel detection means for chronic hydrogen sulfide poisoning.

Development of LC-MS determination method and back-propagation ANN pharmacokinetic model of corynoxeine in rat.

Corynoxeine(CX), isolated from the extract of Uncaria rhynchophylla, is a useful and prospective compound in the prevention and treatment for vascular diseases. A simple and selective liquid chromatography mass spectrometry (LC-MS) method was developed to determine the concentration of CX in rat plasma. The chromatographic separation was achieved on a Zorbax SB-C18 (2.1 mm × 150 mm, 5 μm) column with acetonitrile-0.1% formic acid in water as mobile phase. Selective ion monitoring (SIM) mode was used for quantification using target ions m/z 383 for CX and m/z 237 for the carbamazepine (IS). After the LC-MS method was validated, it was applied to a back-propagation artificial neural network (BP-ANN) pharmacokinetic model study of CX in rats. The results showed that after intravenous administration of CX, it was mainly distributed in blood and eliminated quickly, t1/2 was less than 1h. The predicted concentrations generated by BP-ANN model had a high correlation coefficient (R>0.99) with experimental values. The developed BP-ANN pharmacokinetic model can be used to predict the concentration of CX in rats.

Pharmacokinetics and tissue distribution model of cabozantinib in rat determined by UPLC-MS/MS

Cabozantinib (XL184) is a novel small molecule inhibitor of receptor tyrosine kinases (RTKs) targeted at mesenchymal-epithelial transition factor (MET). In order to study the pharmacokinetics and tissue distribution in rat, a specific ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed with midazolam as internal standard. The calibration curves in plasma and tissues were linear in the range of 5-5000ng/mL (r(2)>0.99). The recoveries were better than 80.4% and matrix effects ranged from 96.9% to 105.1%. Then, the developed UPLC-MS/MS method was applied to determine the concentration of XL184 in blood and tissues. The pharmacokinetics of four different dosages (iv 5, 10mg/kg and ig 15, 30mg/kg) revealed that XL184 was eliminated slowly, the t1/2 was longer than 10h and the absolute bioavailability was 25.6±8.3%. The concentration distribution of XL184 in tissues was liver>lung>kidney>spleen>heart. Based on the concentration-time of XL184 in tissues, a BP-ANN distribution model was developed with good performance, and can be used to predict the concentration of XL184 in tissues.

An efficient machine learning approach for diagnosis of paraquat-poisoned patients

Numerous people die of paraquat (PQ) poisoning because they were not diagnosed and treated promptly at an early stage. Till now, determination of PQ levels in blood or urine is still the only way to confirm the PQ poisoning. In order to develop a new diagnostic method, the potential of machine learning technique was explored in this study. A newly developed classification technique, extreme learning machine (ELM), was taken to discriminate the PQ-poisoned patients from the healthy controls. 15 PQ-poisoned patients recruited from The First Affiliated Hospital of Wenzhou Medical University who had a history of direct contact with PQ and 16 healthy volunteers were involved in the study. The ELM method is examined based on the metabolites of blood samples determined by gas chromatography coupled with mass spectrometry in terms of classification accuracy, sensitivity, specificity and AUC (area under the receiver operating characteristic (ROC) curve) criterion, respectively. Additionally, the feature selection was also investigated to further boost the performance of ELM and the most influential feature was detected. The experimental results demonstrate that the proposed approach can be regarded as a success with the excellent classification accuracy, AUC, sensitivity and specificity of 91.64%, 0.9156%, 91.33% and 91.78%, respectively. Promisingly, the proposed method might serve as a new candidate of powerful tools for diagnosis of PQ-poisoned patients with excellent performance.

Toward an optimal kernel extreme learning machine using a chaotic moth-flame optimization strategy with applications in medical diagnoses

Abstract This study proposes a novel learning scheme for the kernel extreme learning machine ( KELM ) based on the chaotic moth-flame optimization ( CMFO ) strategy. In the proposed scheme, CMFO simultaneously performs parameter optimization and feature selection. The proposed methodology is rigorously compared to several other competitive KELM models that are based on the original moth-flame optimization, particle swarm optimization, and genetic algorithms. The comparison is made using the medical diagnosis problems of Parkinsons disease and breast cancer. And the proposed method has successfully been applied to practical medical diagnosis cases. The experimental results demonstrate that, compared to the alternative methods, the proposed method offers significantly better classification performance and also obtains a smaller feature subset. Promisingly, the proposed CMFOFS - KELM , can serve as an effective and efficient computer aided tool for medical diagnosis in the field of medical decision making.

Liquid chromatography mass spectrometry simultaneous determination of vindoline and catharanthine in rat plasma and its application to a pharmacokinetic study.

Vinblastine and vincristine, both of which are bisindole alkaloids derived from vindoline and catharanthine, have been used for cancer chemotherapy; their monomeric precursor molecules are vindoline and catharanthine. A simple and selective liquid chromatography mass spectrometry method for simultaneous determination of vindoline and catharanthine in rat plasma was developed. Chromatographic separation was achieved on a C18 (2.1u2009×u200950u2009mm, 3.5u2009µm) column with acetonitrile-0.1% formic acid in water as mobile phase with gradient elution. The flow rate was set at 0.4u2009mL/min. An electrospray ionization source was applied and operated in positive ion mode; selective ion monitoring mode was used for quantification. Mean recoveries were in the range of 87.3-92.6% for vindoline in rat plasma and 88.5-96.5% for catharanthine. Matrix effects for vindoline and catharanthine were measured to be between 95.3 and 104.7%. Coefficients of variation of intra-day and inter-day precision were both <15%. The accuracy of the method ranged from 93.8 to 108.1%. The method was successfully applied in a pharmacokinetic study of vindoline and catharanthine in rats. The bioavailability of vindoline and catharanthine were 5.4 and 4.7%, respectively.

Serum Metabolomics in Rats after Acute Paraquat Poisoning

Paraquat is one of the most widely used herbicides in the world and is highly toxic to humans and animals. In this study, we developed a serum metabolomic method based on GC/MS to evaluate the effects of acute paraquat poisoning on rats. Pattern recognition analysis, including both principal component analysis and partial least squares-discriminate analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared with the control group, the level of octadecanoic acid, L-serine, L-threonine, L-valine, and glycerol in the acute paraquat poisoning group (36u2009mg/kg) increased, while the levels of hexadecanoic acid, D-galactose, and decanoic acid decreased. These findings provide an overview of systematic responses to paraquat exposure and metabolomic insight into the toxicological mechanism of paraquat. Our results indicate that metabolomic methods based on GC/MS may be useful to elucidate the mechanism of acute paraquat poisoning through the exploration of biomarkers.