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Background: Lamotrigine (LTG) is a broad-spectrum and first-line anti-epileptic drug. To monitor the serum levels of LTG in epileptic seizures patients, high-performance liquid chromatography with diode-array detection (HPLC-DAD) and ultra-performance liquid chromatography-- tandem mass spectrometry (UPLC-MS/MS) methods were established and compared. Methods: Imatinib was used as the internal standard (IS) for both methods. LTG and IS were detected at 246 nm by HPLC-DAD. In UPLC-MS/MS, LTG and IS positive ion were detected by multiple reaction monitoring (MRM), with m/z of 256/210.9 and 494/394.02, respectively. A total of 37 blood samples from epileptic patients were determined and studied by these two methods. Results: There was an acceptable linearity for the two methods. The concentration range of LTG was 0.59 ~ 22.20 mg/L by HPLC, and 0.28 ~ 23.97 mg/L by UPLC-MS/MS. The Pearson regression coefficient of Deming regression was 0.9653 (95% CI: 0.9332 to 0.9821). Bland–Altman method demonstrated that the concentration of LTG determined by UPLC-MS/MS was 8.3% higher than that determined by HPLC (limits of agreement, -32.0% to +48.6%). Conclusion: There was a significant correlation between the two methods. Both HPLC and UPLC- MS/MS can be used for routine clinical monitoring of LTG.

Alcohol abuse has become a serious health issue worldwide. Ketamine can reduce addiction risk among patients with alcohol use disorders. This study aimed to determine the effects of alcohol on the pharmacokinetics of ketamine during long-term alcohol exposure.An ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for determination of ketamine and norketamine was developed and validated. A total of 15 rats were given 40% alcohol for 3 weeks. The pharmacokinetics of ketamine were measured at time zero, 1 week, 2 weeks, and 3 weeks after alcohol exposure. The metabolic capability of liver CYP450 was evaluated using three probe drugs: metoprolol, phenacetin, and tolbutamide.During drinking of 40% alcohol, the AUC(0-t), AUC(0-∞), and Cmax of ketamine and norketamine significantly increased, while V and CL significantly decreased with time (p 0.001). The pharmacokinetic changes of norketamine were highly consistent with ketamine. Additionally, the concentration ratio of norketamine/ketamine in sample time also decreased over time. However, there were no pharmacokinetic changes of three probe drugs, which indicated there was no significant change of liver CYPs activities.Alcohol significantly increases plasma concentration of ketamine and norketamine. The effect of alcohol on pharmacokinetics of ketamine should be considered in clinical therapy.

Background Millions of adults have been reported with hyperlipemia in the world. It is still unclear whether the plasma level of essential amino acids (AAs) will be influenced by the hyperlipemia. This study was aimed to investigate the AAs levels and the underlying metabolic relationship in hyperlipidemic subjects. Methods An ultra-high performance liquid chromatography-tandem mass spectrometric (UPLC-MS/MS) method was developed for the determination of phenylalanine (Phe), valine (Val), histidine (His), tryptophan (Trp), and methionine (Met). Plasma samples (100 μL) were precipitated by acetonitrile (300 μL) and analyzed on a BEH C18 (2.1 mm × 100 mm, 1.7 μm) column at 40 °C by gradient elution. The mobile phase composed of 0.1% formic acid and acetonitrile was used with flow rate at 0.2–0.4 ml/0-3 min. Five AAs were determined at positive electrospray ionization (ESI+) at m/z 118.1/72.1 (Val), 150.12/104.02(Met), 156.06/110.05(His), 166.1/120.1(Phe), and 205.2/188.02 (Trp). A total of 75 healthy subjects and 83 hyperlipidemic subjects, who had blood routine test and plasma lipid test were determined by developed UPLC-MS/MS. Results It was shown that there was good linearity for Val, Met, His, Phe, and Trp within 1–100 μg/mL. The relative standard deviations of precision and accuracy were all within 15%. The level of Val, Phe, Trp, His, and Met were 35.34 ± 15.64, 22.72 ± 9.13, 17.23 ± 4.94, 16.78 ± 13.64, and 6.24 ± 1.97 μg/mL in healthy subjects, while they were 38.04 ± 16.70, 22.41 ± 8.45, 15.62 ± 5.77, 18.35 ± 14.49, and 6.21 ± 1.97 μg/mL in hyperlipidemic subjects respectively. The Spearman’s correlations analysis showed that there were high correlations between Val, Phe, Trp, His, Met and triglyceride in healthy subjects. While, those correlations decreased in hyperlipemia cases. Conclusion A convenient and sensitive method for simultaneous determination of Val, Phe, Trp, His, and Met in human plasma was developed. There was a high correlation between Val, Phe, Trp, His, Met and triglyceride. Hyperlipemia influences the metabolic balance of His, Phe, Trp, Met and Val.

Background. Hundreds of millions of people worldwide suffer from chronic hepatitis B (CHB), making it one of the most serious public health problems. CHB can lead to serious acute-on-chronic liver failure (ACLF). Since ACLF has a high mortality rate, predicting the risk of ACLF is a critical issue in clinical practice. Methods. To investigate the occurrence of ACLF in CHB, we used high-throughput RNA sequencing to detect the expression of a novel endogenous noncoding RNA (circRNA) in healthy controls (HC) as well as CHB and ACLF patients. Differentially expressed circRNAs were selected and analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analyses, circRNA-miRNA coexpression networks, and statistical analyses. Results. A total of 21,101 circRNAs were identified in HC, CHB, and ACLF subjects. Compared with the HCs, 4 circRNAs were upregulated and 14 circRNAs were downregulated in ACLF subjects, with a consistent trend in all three groups. GO analysis revealed that regulation of lymphocyte activation and macrophage tolerance induction were the most important biological processes in ACLF progression. KEGG pathway analysis revealed that primary immunodeficiency and NOD-like receptor signaling pathways were the most enriched terms. The circRNA-miRNA coexpression network and statistical analyses showed that circRNA_07734, circRNA_08533, and circRNA_16083 were the most important circRNAs in the process of ACLF. Conclusions. Immune dysfunction and deficiency may play a key role in the development of ACLF, especially circRNA_07734, circRNA_08533, and circRNA_16083.

Paraquat (PQ) poisoning seriously harms the health of humanity. An effective diagnostic method for paraquat poisoned patients is a crucial concern. Nevertheless, it's difficult to identify the patients with low intake of PQ or delayed treatment. Here, a new efficient diagnostic approach to integrate machine learning and gas chromatography-mass spectrometry (GC-MS), named GEE, is proposed to identify the PQ poisoned patients. First, GC-MS provides the original data that efficiently identified the paraquat-poisoned patients. According to the high dimensionality of the original data, in the second stage, the chaos enhanced grey wolf optimization (EGWO) is adopted to search the optimal feature sets to improve the accuracy of identification. Finally, the extreme learning machine (ELM) is used to identify the PQ poisoned patients. To efficiently evaluate the proposed method, four measures were used in our experiments and comparisons were made with six other methods. The PQ-poisoned patients and robust volunteers can be well identified by GEE and the values of AUC, accuracy, sensitivity and specificity were 95.14%, 93.89%, 94.44% and 95.83%, respectively. Our experimental results demonstrated that GEE had better performance and might serve as a novel candidate diagnosis of PQ-poisoned patients.

Background Statins play a beneficial role in the treatment of coronary artery disease and are widely prescribed to prevent hypercholesterolemia. Previous studies have demonstrated that statins also have anti-inflammatory and immunomodulatory properties, and these are being explored for potential benefits in depression. However, the role of statins in the treatment of depression has not been well examined. Methods We investigated the effects of simvastatin on depressive behaviors and neuroinflammation in lipopolysaccharide (LPS) and chronic mild stress (CMS) induced depression model in mice. Sucrose preference test (SPT), forced swimming test (FST), novelty-suppressed feeding test (NSFT) were used to detect the depressive behaviors. The microglial activation was detected by immunohistochemistry analysis and the pro-inflammatory cytokines expressions including IL-1β, TNF-α and IL-6 were examined by Western blot analysis. Results Our data indicated that oral administration of simvastatin at 20 mg/kg significantly prevented and ameliorated depressive behaviors reflected by better performance in the SPT, FST and NSFT. Moreover, simvastatin markedly prevented and ameliorated LPS and CMS-induced neuroinflammation, as shown by the suppressed activation of microglia in hippocampus and decreased hippocampal pro-inflammatory cytokines expressions including IL-1β, TNF-α, IL-6, which might be mediated via the inhibition of NF-κB pathway, as shown by the decreased nuclear NF-κB p65 expression. Limitations The interpretation of the evidence of a positive treatment effect of simvastatin on the depressive manifestations, multifaceted etiology of depression, and confirmation of this finding from animal models to humans is needed. Conclusion These results suggest that simvastatin has the potential to be employed as a therapy for depression associated with neuroinflammation.

The biochemical indexes are used to assess the hepatic and renal function of paraquat (PQ) poisoning patients. However, these indexes correlated with the prognosis of patients are unidentified. This paper aims to explore useful indexes from biochemical tests and to identify their predictive value. A total of 101 PQ poisoning patients including 51 dead patients and 50 survived patients is involved in this study. The biochemical indexes of PQ poisoning patients in different status are collected and analyzed by the independent-sample test. After that, Fisher scores feature selection is applied to screen prognostic factors from biochemical indexes. Based on the results of Fisher selection, an effective extreme learning machine (ELM) is applied to diagnose the prognosis status of PQ poisoning patients. The created ELM method is rigorously evaluated for accuracy, sensitivity, and specificity. The results show that there is statistical significance between dead and survived people in biochemical indexes (P

Worldwide, aspirin and ibuprofen are the most commonly used non-steroidal anti-inflammatory drugs (NSAIDs). Some adverse reactions, including gastrointestinal reactions, have been concerned extensively. Nevertheless, the mechanism of liver injury remains unclear. In the present study, we focused on the metabolism of liver cytochrome P450 (CYP450) and ultrastructural morphology of liver cells. A total of thirty rats were divided into three groups of 10. Rats in the aspirin and ibuprofen groups were given enteric-coated aspirin (15 mg/kg) and ibuprofen (15 mg/kg), respectively by gavage for four weeks. The body weights were recorded every two days. Liver function and metabolic capacity of CYP450 were studied on days 14 and 28. We then conducted ultrastructural examinations. Body weights in the Ibuprofen group were lower than those of the Control group, and ALT and AST levels were significantly higher (P 0.05). There were no significant differences in terms of body weight, ALT or AST between the Aspirin and Control groups. The metabolic capacity of CYP450 was evaluated using five probe drugs, phenacetin, tolbutamide, metoprolol, midazolam, and bupropion. We found that ibuprofen and aspirin induced metabolism of the probe drugs. Moreover, according to the pharmacokinetic data, the Control, Aspirin and Ibuprofen groups could be discriminated accurately. Ultrastructural examination showed that the number of mitochondria was increased in both the Ibuprofen and Aspirin groups. Long-term administration of enteric-coated aspirin and ibuprofen induced the metabolic activity of the CYP450 enzyme. Aspirin had better tolerability than did ibuprofen, as reflected by pharmacokinetic data of probe drug metabolism.

Eupatilin, mainly derived from Artemisia asiatica (Asteraceae), is an O-methylated flavone with various bioactivities. In the present study, a validated ultra-performance liquid chromatography–tand...

Hydrogels are excellent drug delivery carriers with excellent ductility. Here, we report the design of a higher biostability of a recombinant human acidic fibroblast growth factor (rh-aFGF) carbomer hydrogel formulation. To verify the optimality of this formula, we prepared various prescriptions and tested the resulting physical properties including micromorphology, long-term stability, accelerated stability, and destructive test. Furthermore, the efficacy for promoting wound healing in full-thickness injury and scald wound diabetic rat models was explored. We found that rh-aFGF-carbomer hydrogel had good physical properties. It was stable for 24 months at 5 ± 3 °C, and for 6 months at 25 ± 3 °C. In vivo, the rh-aFGF-carbomer 940 hydrogel achieved a remarkable promotion of skin wound healing in diabetic rats with full-thickness injuries or scald wounds. Our data suggest that rh-aFGF-carbomer hydrogel may have applications for the treatment of diabetic ulcers combined with other wounds.

Background: Hundreds of millions of people worldwide suffer from chronic hepatitis B (CHB), which is thus among the most serious public health problems. CHB can lead to serious acute chronic liver failure (ACLF). Since ACLF has a very high mortality rate, prediction of ACLF risk is a critical issue in clinical practice. Methods: To investigate the development of ACLF from CHB, circular RNA (circRNA), a novel type of endogenous non-coding RNA, was examined in healthy control (HC) subjects and CHB and ACLF patients using high-throughput RNA sequencing technology. Differentially expressed circRNAs were selected and analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analyses, circRNA-miRNA co-expression networks, and statistical analyses. Results: A total of 21,101 circRNAs were identified in HC, CHB and ACLF subjects. Compared with the HCs, 4 up-regulated and 14 down-regulated circRNAs were identified in ACLF subjects, which exhibited a consistent trend of change in the three groups. GO analysis revealed that regulation of lymphocyte activation and macrophage tolerance induction were the most important biological processes in ACLF progression. KEGG pathway analysis revealed that primary immunodeficiency and NOD-like receptor signaling pathways were the most enriched terms. The circRNA-miRNA co-expression network and statistical analyses showed that circRNA_07734, circRNA_08533, and circRNA_16083 were the most important circRNAs in the process of ACLF. Conclusions: Immune dysfunction and immunodeficiency may be critical in the development of ACLF, which results in aberrant expression of circRNAs, especially circRNA_07734, circRNA_08533, and circRNA_16083.

BACKGROUND Paraquat ( PQ) is very poisonous to humans and animals and there is no effective clinical antidote . The efficacy of hemoperfusion (HP) treatment for PQ poisoning remains controversial. To explore new ways to predict the prognosis of patients with acute PQ poisoning and assist in the development of better hemopurification treatment strategies. METHODS The clinical data of patients who were intoxicated with PQ through contact were diagnosed with PQ poisoning by high-performance liquid chromatography. Samples were collected by the Emergency Intensive Care Unit of the First Affiliated Hospital of Wenzhou Medical University from January 2012 to November 2016. Based on the prognosis, the patients were grouped into survival and death groups. Comparisons of the differences in the clinical indexes were performed, including the initial concentration of PQ at admission, PQ concentration after first HP, the number of HP cartridges used for the first hemoperfusion, whether HP was combined with continuous renal replacement therapy, and the number of concurrent organ injuries between the 2 groups. In addition, data were analyzed using multivariate logistic regression models and receiver operating characteristic curves. Moreover, prognostic factors in patients with acute PQ poisoning were analyzed. RESULTS Overall, 128 patients with acute PQ poisoning were enrolled in this study. The median plasma PQ concentrations of the patients at admission were 21 and 834 ng/mL (range: 50-1,099,118 ng/mL). The multiple logistic regression model revealed that the initial concentration of PQ and the PQ concentration after the first perfusion were independent risk factors for death in patients with acute PQ poisoning. The PQ concentration in the survival group after the first HP was

Additional file 1 Supplement Table 1 The equation of calibration curves of 5 AAs in human plasma

Additional file 1. SPIRIT checklist.

Additional file 5 Supplement Table 5 Peaks area of 5 AAs (10 μg/mL) in pure standard and blood sample determined by Hilic and BEH C18 column

Additional file 4 Supplement Table 4 RSD values of ruggedness determined on two different columns and by different analysts

Additional file 2 Supplement Table 2 The extraction recovery, matrix effect and stability of 5 AA in human plasma (n = 3)

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 Parkinson's 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.

In this study, we developed a serum and urine metabolomic method based on gas chromatography-mass spectrometry (GC-MS) combination with biomedical results to evaluate the effect of vitamin E treatment on methomyl poisoning rats. The rats were divided into three groups: the control group, methomyl poisoning group, and vitamin E treatment group. Partial least squares discriminate analysis (PLS-DA) showed that methomyl poisoning induced metabolic perturbations. Compared to the control group, based on the urinary metabolomics data, the level of ribitol, l-proline, xylitol, hydrocinnamic acid, 11-cis-octadecenoic acid, octadecanoic acid, and hexadecanoic acid of methomyl poisoning group increased, while the level of 2,3,4-trihydroxybutyric acid, ethanimidic acid, pantothenic acid, and retinoic acid decreased. Vitamin E pretreatment effectively normalized the levels of metabolites in rat urine in vitamin E treatment group. There was no significant difference in rat plasma metabolomic data after acute methomyl poisoning. The results indicate that metabolomic method based on GC-MS may be useful to elucidate the vitamin E treatment for methomyl poisoning.

Background: Aspirin and ibuprofen are the most frequently prescribed non-steroidal anti-inflammatory drugs in the world. However, both are associated with a variety of toxicities. We applied serum metabonomics and Fisher discrimination for the early diagnosis of its toxic reaction in order to help diagnose these toxicities. Methods: A total of 45 rats were randomly divided into Control group, Aspirin group, and Ibuprofen groups. The experiment groups were given intragastric aspirin (15 mg/kg) or ibuprofen (15 mg/kg) for 3 weeks. Liver function tests were performed and blood metabonomics were analyzed by gas chromatography-mass spectrometry. Results: The most important compounds altered were trihydroxybutyric acid and l-alanine in the aspirin group, and acetoacetic acid, l-alanine, and trihydroxybutyric acid in the ibuprofen group. With respect to metabolic profiles, all 3 groups were completely distinct from one another. Fisher discrimination showed that 91.1% of the original grouped cases were correctly classified by the third week. However, only 55.6% of liver function tests were able to classify grouped cases correctly. Conclusion: Trihydroxybutyric acid, l-alanine, and acetoacetic acid were the most significant indicators of altered serum metabolites following intragastric administration of aspirin and ibuprofen in rates. These metabolomic data may be used for classification of aspirin and ibuprofen toxicity.

Most paraquat (PQ) poisoned patients died from acute multiple organ failure (MOF) such as lung, kidney, and heart. However, the exact mechanism of intoxication is still unclear. In order to find out the initial toxic mechanism of PQ poisoning, a blood metabolomics study based on ultraperformance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and efficient machine learning approach was performed on 23 PQ poisoned patients and 29 healthy subjects. The initial PQ plasma concentrations of PQ poisoned patients were >1000 ng/mL, and the blood samples were collected at before first hemoperfusion (HP), after first HP, and after last HP. The results showed that PQ poisoned patients all differed from healthy subjects, whatever they were before or after first HP or after last HP. The efficient machine learning approaches selected key metabolites from three UPLC/Q-TOF-MS data sets which had the highest classification performance in terms of classification accuracy, Matthews Correlation Coefficients, sensitivity, and specificity, respectively. The mass identification revealed that the most important metabolite was adenosine, which sustained in low level, regardless of whether PQ poisoned patients received HP treatment. In conclusion, decreased adenosine was the most important metabolite in PQ poisoned patients. The metabolic disturbance caused by PQ poisoning cannot be improved by HP treatment even the PQ was cleared from the blood.

Background HOTAIR is a variety of long non-coding RNA that has been recognized as a predictive factor for most cancers. This meta-analysis examined the complete investigative effectiveness of the level of HOTAIR expression for various cancers. Methods Research on the diagnostic value of HOTAIR in different carcinomas was acquired by searching the online databases. Twelve studies consisting of 927 cancer cases were chosen in our research. The sensitivity as well as specificity of the involved articles was helpful to establish the summary receiver operator characteristic (SROC) curve in addition to compute the area under the SROC curve (AUC). In addition, a meta-regression test was done to determine the heterogeneity sources among available studies. Results The combined effect sizes calculated from involved studies were as follows: sensitivity, 0.73; specificity, 0.83; PLR, 4.4; NLR, 0.32; DOR, 14; and an AUC of 0.85. Deeks' funnel plot asymmetry test showed no probable publication bias. The meta-regression analyses signified that the type of ethnicity is the major cause of heterogeneity. Conclusions The present meta-analysis suggested that elevated HOTAIR can be considered as a relatively accurate marker for cancer diagnosis and can be applied to support the diagnosis of various cancers.

The diagnosis of paraquat-poisoned patients is one of the important problems in the medical diagnosis field. Current methods identify the paraquat-poisoned patients mainly depending on paraquat con...

Self-assembled polymeric micelles have been widely applied in anticancer drug delivery systems. Teniposide is a broad spectrum and effective anticancer drug, but its poor water-solubility and adverse effects of commercial formulation (VM-26) restrict its clinical application. In this work, teniposide-loaded polymeric micelles were prepared based on monomethoxy-poly(ethylene glycol)-poly(e-caprolactone-co-d,l- lactide) (MPEG-PCLA) copolymers through a thin-film hydration method to improve the hydrophilic and reduce the systemic toxicity. The prepared teniposide micelles were without any surfactants or additives and monodisperse with a mean particle size of 29.6±0.3nm. The drug loading and encapsulation efficiency were 18.53±0.41% and 92.63±2.05%, respectively. The encapsulation of teniposide in MPEG-PCLA micelles showed a slow and sustained release behavior of teniposide in vitro and improved the terminal half-life (t1/2), the area under the plasma concentration-time curve (AUC) and retention time of teniposide in vivo compared with VM-26. In addition, teniposide micelles also enhanced the cellular uptake by MCF-7 breast cancer cells in vitro and increased the distribution in tumors in vivo. Teniposide micelles showed an excellent safety with a maximum tolerated dose (MTD) of approximately 50mg teniposide/kg body weight, which was 2.5-fold higher than that of VM-26 (about 20mg teniposide/kg body weight). Furthermore, the intravenous application of teniposide micelles effectively suppressed the growth of subcutaneous MCF-7 tumor in vivo and exhibited a stronger anticancer effect than that of VM-26. These results suggested that we have successfully prepared teniposide-loaded MPEG-PCLA micelles with improved safety, hydrophilic and therapeutic efficiency, which are efficient for teniposide delivery. The prepared teniposide micelles may be promising in breast cancer therapy.

The early identification of toxic paraquat (PQ) poisoning in patients is critical to ensure timely and accurate prognosis. Although plasma PQ concentration has been reported as a clinical indicator of PQ poisoning, it is not commonly applied in practice due to the inconvenient necessary instruments and operation. In this study, we explored the use of blood routine indexes to identify the degree of PQ toxicity and/or diagnose PQ poisoning in patients via machine learning approach. Specifically, we developed a method based on support vector machine combined with the feature selection technique to accurately predict PQ poisoning risk status, then tested the method on 79 (42 male and 37 female; 41 living and 38 deceased) patients. The detection method was rigorously evaluated against a real-world data set to determine its accuracy, sensitivity and specificity. Feature selection was also applied to identify the factors correlated with risk status, and the results showed that there are significant differences in blood routine indexes between dead and living PQ-poisoned individuals (p-value < 0.01). Feature selection also showed that the most important correlated indexes are white blood cell and neutrophils. In conclusion, the toxicity or prognosis of PQ poisoning can be preliminarily ascertained by blood routine testing without PQ concentration data, representing an additional tool and innovative approach to assess the prognosis of PQ poisoning.

Overweight individuals are at higher risk for developing type II diabetes than the general population. We conducted this study to analyze the correlation between blood glucose and biochemical parameters, and developed a blood glucose prediction model tailored to overweight patients.A total of 346 overweight Chinese people patients ages 18-81 years were involved in this study. Their levels of fasting glucose (fs-GLU), blood lipids, and hepatic and renal functions were measured and analyzed by multiple linear regression (MLR). Based the MLR results, we developed a back propagation artificial neural network (BP-ANN) model by selecting tansig as the transfer function of the hidden layers nodes, and purelin for the output layer nodes, with training goal of 0.5×10(-5).There was significant correlation between fs-GLU with age, BMI, and blood biochemical indexes (P0.05). The results of MLR analysis indicated that age, fasting alanine transaminase (fs-ALT), blood urea nitrogen (fs-BUN), total protein (fs-TP), uric acid (fs-BUN), and BMI are 6 independent variables related to fs-GLU. Based on these parameters, the BP-ANN model was performed well and reached high prediction accuracy when training 1 000 epoch (R=0.9987).The level of fs-GLU was predictable using the proposed BP-ANN model based on 6 related parameters (age, fs-ALT, fs-BUN, fs-TP, fs-UA and BMI) in overweight patients.

• Amino acids (AAs) are abundant in seminal fluid and play an important role in the reproduction process. However, the functional significance of AAs in seminal is not clear. This study was designed to profile the AAs in seminal fluid of asthenozoospermia (AS) and oligospermia (OL) patients and evaluate its potential diagnostic value. To determine the true function of AAs in seminal fluid, an ultra high performance liquid chromatography-mass spectrometry (UPLC-MS/MS) was developed and validated. The seminal fluid samples collected from 76 AS patients, 58 OL patients, and 76 healthy subjects were determined by UPLC-MS/MS and analyzed by fisher discriminant and receiver operating characteristic (ROC). The results showed that, the AAs levels were dramatically decreased in AS and OL patients compared with healthy subjects. What’s more there were significant variation in the AAs profile of AS and OL patients. Specifically, some polar AAs decreased, while nonpolar AAs increased in OL patients. Based on the level of AAs, 93.4 % of original and 90.9 % of cross-validated grouped cases were correctly classified between AS patients, OL patients, and healthy subjects. The further ROC analysis shows that glutamic acid, tyrosine, aspartic acid, proline, and tryptophan have the diagnostic value (P 0.9) in AS, OL, and healthy subjects. In conclusion, there are significant variation in AAs profile in seminal plasma of AS and OL patients with high accuracy in fisher classification. The associations between the levels of AAs in seminal fluid of AS, OL, and healthy subjects may have clinical applications in providing valuable diagnostic indicator.

Supplementary_Table for Diagnostic value of complete blood count in paraquat and organophosphorus poisoning patients by Yahui Tang, Lufeng Hu, Guangliang Hong, Dahai Zhong, Jiaxing Song, Guangju Zhao and Zhongqiu Lu in Toxicology and Industrial Health

Linezolid has been widely used in serious infections for its effective inhibiting effect against multidrug-resistant gram-positive pathogens. However, linezolid caused severe adverse reactions, such as thrombocytopenia, anaemia, optic neuropathy, and near-fatal serotonin syndrome. In order to investigate the toxicity of linezolid, twenty-four Sprague-Dawley rats were randomly divided into: control group (n=7), low-group (n=8), and high-group (n=9). The rats of low-group and high-group were given by gavage with linezolid 60 and 120 mg/kg/day for 7 days, respectively. The serum concentration of linezolid was determined by high performance liquid chromatography (HPLC); blood metabolic change was analyzed by gas chromatography-mass spectrometer (GC-MS). Adenosine triphosphate (ATP) concentration in HepG2-C3A after being cultured with linezolid was determined by HPLC. The results showed that there were six metabolites and nine metabolites had statistical differences in low-group and high-group (Pα-linolenic acid, eicosapentaenoic acid, 9,12-Octadecadienoic acid, and docosahexaenoic acid were all decreased in low-group and high-group. ATP concentration was decreased in HepG2-C3A after cultured with linezolid. In conclusion, the toxicity of linezolid is related to its serum concentration. Linezolid may inhibit the synthesis of ATP and fatty acid.

Paraquat is quick-acting and non-selective, killing green plant tissue on contact; it is also toxic to human beings and animals. In this study, we developed a urine metabonomic method by gas chromatography-mass spectrometry to evaluate the effect of acute paraquat poisoning on rats. Pattern recognition analysis, including both partial least squares discriminate analysis and principal component analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared with the control group, the levels of benzeneacetic acid and hexadecanoic acid of the acute paraquat poisoning group (intragastric administration 36 mg/kg) increased, while the levels of butanedioic acid, pentanedioic acid, altronic acid decreased. Based on these urinary metabolomics data, support vector machine was applied to discriminate the metabolomic change of paraquat groups from the control group, which achieved 100% classification accuracy. In conclusion, metabonomic method combined with support vector machine can be used as a useful diagnostic tool in paraquat-poisoned rats.

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.

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.

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 (n = 60) differed significantly from the control group (n = 30), 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.

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. A novel method is presented for diagnosis of paraquat (PQ) poisoning.The key parameters involved in ELM have been investigated in detail.The effectiveness of the proposed method has been rigorously evaluated.The approach has detected the most influential feature account for PQ poisoning.

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.

Numerous people die of paraquat (PQ) poisoning every year in the world. Although several studies regarding paraquat (PQ) poisoning have been conducted, the metabolic changes in plasma remain unknown. In this study, the metabolomics of 15 PQ poisoned patients with plasma PQ concentrations in excess of 0.1 µg/mL and 16 healthy volunteers were investigated. The plasma samples were evaluated through the use of gas chromatography-mass spectrometry (GC/MS) and analyzed by partial least-squares discriminant analysis (PLS-DA). Based on the metabolomics data, a support vector machine (SVM) discrimination model was developed. The results showed the plasma levels of urea, glucose oxime and L-phenylalanine decreased and cholesterol increased in PQ poisoned patients in comparison to healthy volunteers. The SVM discrimination model was developed, and performed with a high degree of accuracy, to distinguish PQ poisoned patients from healthy volunteers. In conclusion, metabolic pathways including the urea cycle, and amino acid, glucose, and cholesterol metabolism were impaired after PQ poisoning. An SVM discrimination model, based on metabolomics data, was established and may become a new powerful tool for the diagnosis of PQ poisoning.