The relationship between mean corpuscular hemoglobin concentration and mortality in hypertensive individuals: A population-based cohort study.

INTRODUCTION: Hematology is an essential field for investigating the prognostic outcomes of cardiovascular diseases (CVDs). Recent research has suggested that mean corpuscular hemoglobin concentration (MCHC) is associated with a poor prognosis in several CVDs. There is no evidence of a correlation between MCHC and hypertension. Therefore, our study aimed to analyze the association of MCHC with all-cause and cardiovascular mortality in hypertensive patients. METHODS: We used cohort data from U.S. adults who participated in the National Health and Nutrition Examination Survey from 1999-2014. COX regression was applied to analyze the relationship between MCHC and all-cause and cardiovascular mortality. In addition, three models were adjusted to reduce confounding factors. We reanalyzed the data after propensity score matching (PSM) to inspect the stability of the results. Stratified analysis was additionally adopted to investigate the results of each subgroup. RESULTS: Our research included 15,154 individuals. During a mean follow-up period of 129 months, 30.6% of the hypertensive population succumbed to mortality. Based on previous studies, we categorized patients with MCHC ≤33mg/dl as the hypochromia group and those with >33mg/dl as the non-hypochromia group. After PSM, the hypochromia group had higher all-cause mortality (adjusted hazard ratio [HR]:1.26, 95% confidence interval [95%CI]:1.11-1.43) and cardiovascular mortality (adjusted HR:1.42, 95%CI:1.12-1.80) than the non-hypochromia group. The results of the COX regression remain stable after matching. Stratified analyses before PSM revealed an interaction of anemia in the relationship between MCHC and mortality, whereas there was no significant interaction after matching. CONCLUSION: In hypertensive individuals, low MCHC was correlated with a poor prognosis. Further studies on MCHC are necessary to analyze the potential mechanisms of its poor prognosis in hypertensive populations.

Cd-MOF and Its Ln3+-Post Modification Products: Regulation of Luminescence Properties and Improved Detection of Uric Acid, Quinine, and Quinidine.

One 3D Cd-MOF, namely, {[(HDMA)2][Cd3(L)2]·5H2O·2DMF}n (LCU-124, LCU indicates Liaocheng University), was synthesized from an ether-containing ligand 1,3-bis(3,5-dicarboxylphenoxy)benzene (H4L). Its Ln3+-postmodified samples, Eu3+@LCU-124 and Tb3+@LCU-124, were obtained through cation exchange of dimethylamine cation (HDMA) with Eu3+ and Tb3+. The successful entry of rare earth into LCU-124 by cation exchange modification was verified by IR, XRD, XPS, EDS mapping, and luminescence spectra. The proportion of Eu3+/Tb3+ was adjusted during the modification process, leading to fluorescent materials with different emissions. Luminescence measurements indicated that these complexes exhibited interesting multiresponsive sensing activities toward biomarkers urine acid (UA), quinine (QN), and quinidine (QND). First, LCU-124 has a pronounced quenching effect toward UA with the detection limit of 31.01 µM. After modification, the visualization of the detection was improved significantly and the detection limit of Eu3+@LCU-124 was reduced to 0.868 µM. Second, when QN and QND were present in the suspensions of Eu3+@LCU-124 and Tb3+@LCU-124, strong blue light emission peaks occurred, while the characteristic emission of Eu3+/Tb3+ decreased, forming ratiometric fluorescent sensors with the detection limit in the range of 0.199-9.49 µM. The fluorescent probes have high selectivity, excellent sensitivity recycling, and fast response time (less than 1 min). Besides, a simple logic gate circuit and a range of luminescent mixed matrix membranes were designed to provide simple and fast detection of above biomarkers. Our work indicated that modification of Eu3+/Tb3+ could improve the detection ability significantly.

A Relationship Prediction Method for Magnaporthe oryzae-Rice Multi-Omics Data Based on WGCNA and Graph Autoencoder.

Magnaporthe oryzae Oryzae (MoO) pathotype is a devastating fungal pathogen of rice; however, its pathogenic mechanism remains poorly understood. The current research is primarily focused on single-omics data, which is insufficient to capture the complex cross-kingdom regulatory interactions between MoO and rice. To address this limitation, we proposed a novel method called Weighted Gene Autoencoder Multi-Omics Relationship Prediction (WGAEMRP), which combines weighted gene co-expression network analysis (WGCNA) and graph autoencoder to predict the relationship between MoO-rice multi-omics data. We applied WGAEMRP to construct a MoO-rice multi-omics heterogeneous interaction network, which identified 18 MoO small RNAs (sRNAs), 17 rice genes, 26 rice mRNAs, and 28 rice proteins among the key biomolecules. Most of the mined functional modules and enriched pathways were related to gene expression, protein composition, transportation, and metabolic processes, reflecting the infection mechanism of MoO. Compared to previous studies, WGAEMRP significantly improves the efficiency and accuracy of multi-omics data integration and analysis. This approach lays out a solid data foundation for studying the biological process of MoO infecting rice, refining the regulatory network of pathogenic markers, and providing new insights for developing disease-resistant rice varieties.

The relationship between preserved ratio impaired spirometry and mortality in the myocardial infarction survivors: a population-based cohort study.

INTRODUCTION: Preserved ratio impaired spirometry (PRISm) is a subtype of pulmonary function abnormality which is characterized by a proportional reduction in non-obstructive expiratory lung volume. Currently, no studies have shown a relationship between PRISm and mortality in myocardial infarction (MI) survivors. METHODS: We used cohort data from U.S. adults who attended the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2012. According to the ratio of forced expiratory volume in the first second (FEV1) to forced vital capacity (FVC), we divided lung function into normal spirometry (FEV1/ FVC) ≥ 70%, FEV1 ≥ 80%), PRISm (FEV1/FVC ≥ 70%, FEV1 < 80%) and obstructive spirometry (FEV1/FVC < 70%). Cox regression was used to estimate the correlation between lung functions and mortality among MI patients. Kaplan-Meier survival curves compared the prognosis of MI with three different lung functions. We further verify the stability of the results by sensitivity analysis. RESULTS: 411 subjects were included in our research. The mean follow-up time for the study was 105 months. Compared with normal spirometry, PRISm was significantly correlated with a greater relative risk for all-cause mortality (adjust HR 3.41, 95% confidence interval [95%CI]: 1.76-6.60, P < 0.001) and cardiovascular mortality (adjust HR 13.9, 95%CI: 2.60-74.6, P = 0.002). PRISm remains more correlated with all-cause mortality (adjust HR 2.73, 95%CI: 1.28-5.83, P = 0.009) relative to obstructive spirometry. The results are basically stable after sensitivity analysis. Kaplan-Meier survival curves showed that patients with PRISm tended to have the lowest survival during the follow-up period. CONCLUSION: PRISm is an independent risk factor for all-cause and cardiovascular mortality in MI survivors. The presence of PRISm was associated with a significantly higher risk of all-cause mortality compared with obstructive spirometry.

Corrigendum: Research on the mechanism of soybean resistance to Phytophthora infection using machine learning Methods.

[This corrects the article DOI: 10.3389/fgene.2021.634635.].

Determining the interlayer shearing in twisted bilayer MoS2 by nanoindentation.

The rise of twistronics has increased the attention of the community to the twist-angle-dependent properties of two-dimensional van der Waals integrated architectures. Clarification of the relationship between twist angles and interlayer mechanical interactions is important in benefiting the design of two-dimensional twisted structures. However, current mechanical methods have critical limitations in quantitatively probing the twist-angle dependence of two-dimensional interlayer interactions in monolayer limits. Here we report a nanoindentation-based technique and a shearing-boundary model to determine the interlayer mechanical interactions of twisted bilayer MoS2. Both in-plane elastic moduli and interlayer shear stress are found to be independent of the twist angle, which is attributed to the long-range interaction of intermolecular van der Waals forces that homogenously spread over the interfaces of MoS2. Our work provides a universal approach to determining the interlayer shear stress and deepens the understanding of twist-angle-dependent behaviours of two-dimensional layered materials.

A Multi-Level Iterative Bi-Clustering Method for Discovering miRNA Co-regulation Network of Abiotic Stress Tolerance in Soybeans.

Although growing evidence shows that microRNA (miRNA) regulates plant growth and development, miRNA regulatory networks in plants are not well understood. Current experimental studies cannot characterize miRNA regulatory networks on a large scale. This information gap provides an excellent opportunity to employ computational methods for global analysis and generate valuable models and hypotheses. To address this opportunity, we collected miRNA-target interactions (MTIs) and used MTIs from Arabidopsis thaliana and Medicago truncatula to predict homologous MTIs in soybeans, resulting in 80,235 soybean MTIs in total. A multi-level iterative bi-clustering method was developed to identify 483 soybean miRNA-target regulatory modules (MTRMs). Furthermore, we collected soybean miRNA expression data and corresponding gene expression data in response to abiotic stresses. By clustering these data, 37 MTRMs related to abiotic stresses were identified, including stress-specific MTRMs and shared MTRMs. These MTRMs have gene ontology (GO) enrichment in resistance response, iron transport, positive growth regulation, etc. Our study predicts soybean MTRMs and miRNA-GO networks under different stresses, and provides miRNA targeting hypotheses for experimental analyses. The method can be applied to other biological processes and other plants to elucidate miRNA co-regulation mechanisms.

Exploring the Common Mechanism of Fungal sRNA Transboundary Regulation of Plants Based on Ensemble Learning Methods.

Studies have found that pathogenic fungi and plants have sRNA transboundary regulation mechanisms. However, no researchers have used computer methods to carry out comprehensive studies on whether there is a more remarkable similarity in the transboundary regulation of plants by pathogenic fungi. In this direction, high-throughput non-coding sRNA data of three types of fungi and fungi-infected plants for 72 h were obtained. These include the Magnaporthe, Magnaporthe oryzae infecting Oryza sativa, Botrytis cinerea, Botrytis cinerea infecting Solanum lycopersicum, Phytophthora infestans and Phytophthora infestans infecting Solanum tuberosum. Research on these data to explore the commonness of fungal sRNA transboundary regulation of plants. First, using the big data statistical analysis method, the sRNA whose expression level increased significantly after infection was found as the key sRNA for pathogenicity, including 355 species of Magnaporthe oryzae, 399 species of Botrytis cinerea, and 426 species of Phytophthora infestans. Secondly, the target prediction was performed on the key sRNAs of the above three fungi, and 96, 197, and 112 core nodes were screened out, respectively. After functional enrichment analysis, multiple GO and KEGG_Pathway were obtained. It is found that there are multiple identical GO and KEGG_Pathway that can participate in plant gene expression regulation, metabolism, and other life processes, thereby affecting plant growth, development, reproduction, and response to the external environment. Finally, the characteristics of key pathogenic sRNAs and some non-pathogenic sRNAs are mined and extracted. Five Ensemble learning algorithms of Gradient Boosting Decision Tree, Random Forest, Adaboost, XGBoost, and Light Gradient Boosting Machine are used to construct a binary classification prediction model on the data set. The five indicators of accuracy, recall, precision, F1 score, and AUC were used to compare and analyze the models with the best parameters obtained by training, and it was found that each model performed well. Among them, XGBoost performed very well in the five models, and the AUC of the validation set was 0.86, 0.93, and 0.90. Therefore, this model has a reference value for predicting other fungi's key sRNAs that transboundary regulation of plants.

Construction of sRNA Regulatory Network for Magnaporthe oryzae Infecting Rice Based on Multi-Omics Data.

Studies have shown that fungi cause plant diseases through cross-species RNA interference mechanism (RNAi) and secreted protein infection mechanism. The small RNAs (sRNAs) of Magnaporthe oryzae use the RNAi mechanism of rice to realize the infection process, and different effector proteins can increase the autotoxicity by inhibiting pathogen-associated molecular patterns triggered immunity (PTI) to achieve the purpose of infection. However, the coordination of sRNAs and proteins in the process of M. oryzae infecting rice is still poorly understood. Therefore, the combination of transcriptomics and proteomics to study the mechanism of M. oryzae infecting rice has important theoretical significance and practical value for controlling rice diseases and improving rice yields. In this paper, we used the high-throughput data of various omics before and after the M. oryzae infecting rice to screen differentially expressed genes and sRNAs and predict protein interaction pairs based on the interolog and the domain-domain methods. We were then used to construct a prediction model of the M. oryzae-rice interaction proteins according to the obtained proteins in the proteomic network. Finally, for the differentially expressed genes, differentially expressed sRNAs, the corresponding mRNAs of rice and M. oryzae, and the interacting protein molecules, the M. oryzae-rice sRNA regulatory network was built and analyzed, the core nodes were selected. The functional enrichment analysis was conducted to explore the potential effect pathways and the critical infection factors of M. oryzae sRNAs and proteins were mined and analyzed. The results showed that 22 sRNAs of M. oryzae, 77 secretory proteins of M. oryzae were used as effect factors to participate in the infection process of M. oryzae. And many significantly enriched GO modules were discovered, which were related to the infection mechanism of M. oryzae.

Construction of Smart City Street Landscape Big Data-Driven Intelligent System Based on Industry 4.0.

With the application of engineering management in smart city construction under Industry 4.0, the intelligent design of urban street landscape has attracted extensive attention. Affected by the low intelligent level of traditional landscape design, the existing urban landscape composite system has difficulty in meeting the needs of smart city construction. Therefore, this paper proposes the construction of street landscape big data-driven intelligent decision support system based on Industry 4.0. Based on the complex network theory, this paper analyzes the structure, links, nodes, driving forces, and functional requirements of urban street landscape and then puts forward the construction content and implementation method of urban street landscape intelligent decision support system. The system consists of four aspects: intelligent infrastructure, service, protection and maintenance, and management and evaluation system. Its implementation not only reflects the cooperation and effective application of intelligent technology in each stage of street landscape construction, but also provides reference for the application of engineering management in other fields under Industry 4.0.

Curcumin suppresses the progression of gastric cancer by regulating circ_0056618/miR-194-5p axis.

Curcumin has been demonstrated to be an anti-tumor agent in many types of cancers, including gastric cancer (GC). However, the molecular mechanisms by which curcumin performs its anti-tumor effects remain elusive. circ_0056618 and miR-194-5p are reported to be involved in GC progression, but their relationships with curcumin are unclear. In this study, circ_0056618 was elevated, and miR-194-5p was reduced in GC tissues and cells. Curcumin treatment led to a decrease in circ_0056618 level in GC cells. Overexpression of circ_0056618 promoted cell proliferation, migration, and invasion and suppressed cell cycle arrest and apoptosis in curcumin-treated GC cells. Moreover, miR-194-5p was identified as the target of circ_0056618, and its expression in GC cells increased after curcumin treatment. Overexpression of miR-194-5p reversed the promotional effect of circ_0056618 on cell progression in curcumin-treated GC cells. Additionally, curcumin treatment repressed the tumorigenesis of GC in vivo through regulating circ_0056618. Curcumin treatment delayed the development of GC partly through decreasing circ_0056618 and increasing miR-194-5p.

Research on the Mechanism of Soybean Resistance to Phytophthora Infection Using Machine Learning Methods.

Since the emergence of the Phytophthora sojae infection, economic losses of 10-20 billion U.S. dollars have been annually reported. Studies have revealed that P. sojae works by releasing effect factors such as small RNA in the process of infecting soybeans, but research on the interaction mechanism between plants and fungi at the small RNA level remains vague and unclear. For this reason, studying the resistance mechanism of the hosts after P. sojae invades soybeans has critical theoretical and practical significance for increasing soybean yield. The present article is premised on the high-throughput data published by the National Center of Biotechnology Information (NCBI). We selected 732 sRNA sequences through big data analysis whose expression level increased sharply after soybean was infected by P. sojae and 36 sRNA sequences with massive expression levels newly generated after infection. This article analyzes the resistance mechanism of soybean to P. sojae from two aspects of plant's own passive stress and active resistance. These 768 sRNA sequences are targeted to soybean mRNA and P. sojae mRNA, and 2,979 and 1,683 targets are obtained, respectively. The PageRank algorithm was used to screen the core functional clusters, and 50 core nodes targeted to soybeans were obtained, which were analyzed for functional enrichment, and 12 KEGG_Pathway and 18 Go(BP) were obtained. The node targeted to P. sojae was subjected to functional enrichment analysis to obtain 11 KEGG_Pathway. The results show that there are multiple Go(BP) and KEGG_Pathway related to soybean growth and defense and reverse resistance of P. sojae. In addition, by comparing the small RNA prediction model of soybean resistance with Phytophthora pathogenicity constructed by the three machine learning methods of random forest, support vector machine, and XGBoost, about the accuracy, precision, recall rate, and F-measure, the results show that the three models have satisfied classification effect. Among the three models, XGBoost had an accuracy rate of 86.98% in the verification set.

Transboundary Pathogenic microRNA Analysis Framework for Crop Fungi Driven by Biological Big Data and Artificial Intelligence Model.

Plant fungal diseases have been affecting the world's agricultural production and economic levels for a long time, such as rice blast, gray tomato mold, potato late blight etc. Recent studies have shown that fungal pathogens transmit microRNA as an effector to host plants for infection. However, bioassay-based verification analysis is time-consuming and challenging, and it is difficult to analyze from a global perspective. With the accumulation of fungal and plant-related data, data analysis methods can be used to analyze pathogenic fungal microRNA further. Based on the microRNA expression data of fungal pathogens infecting plants before and after, this paper discusses the selection strategy of sample data, the extraction strategy of pathogenic fungal microRNA, the prediction strategy of a fungal pathogenic microRNA target gene, the bicluster-based fungal pathogenic microRNA functional analysis strategy and experimental verification methods. A general analysis pipeline based on machine learning and bicluster-based function module was proposed for plant-fungal pathogenic microRNA.The pipeline proposed in this paper is applied to the infection process of Magnaporthe oryzae and the infection process of potato late blight. It has been verified to prove the feasibility of the pipeline. It can be extended to other relevant crop pathogen research, providing a new idea for fungal research on plant diseases. It can be used as a reference for understanding the interaction between fungi and plants.

Percutaneous Coronary Intervention Compared with Coronary Artery Bypass Graft Surgery for Patients With 3-vessel Disease: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses-compliant Systematic Review and Meta-analysis.

OBJECTIVES: Previous investigations showed inconsistent results for comparison in clinical outcomes between patients with 3-vessel disease (3VD) treated with percutaneous coronary intervention (PCI) and coronary artery bypass graft (CABG) surgery. A systematic review and meta-analysis is essential to compare the clinical outcomes of PCI with CABG surgery for patients with 3VD. METHODS: We systematically searched on PubMed and Web of Science for articles which compared PCI with CABG for patients with 3VD and published from January 1989 to January 2020. We computed the hazard ratios (HRs) and 95% confidence intervals (CIs) for individual clinical outcomes. RESULTS: This study indicated that the PCI group was associated with a 1.51-fold higher risk of all-cause mortality compared with the CABG group in patients with 3VD (HR 1.51, 95% CI 1.38-1.65). In addition, the PCI group showed a 3.08-fold and 2.94-fold higher risk compared with the CABG group in risks of myocardial infarction (MI) and target-vessel revascularization (TVR), respectively (MI: HR 3.08, 95% CI 2.61-3.63; TVR: HR 2.94, 95% CI 1.94-4.46). CONCLUSIONS: In conclusion, in patients with 3VD, PCI was consistently associated with higher rates of all-cause mortality, MI, and TVR, compared with CABG.

lncRNA-XIST protects the hypoxia-induced cardiomyocyte injury through regulating the miR-125b-hexokianse 2 axis.

Ischemic injury in the heart is associated with low oxygen, leading to the damage of cardiomyocytes. The lncRNA-XIST is known to involve in post-ischemia myocardial remodeling. However, the roles and mechanism of XIST in the hypoxia-induced cardiomyocyte are still under investigation. Moreover, studies that elucidated the impaired glucose metabolism present new hallmark of ischemic cardiovascular injury. The objective of this study is to investigate the effects of lncRNA-XIST on cardiomyocyte injury under hypoxia. Here, we demonstrate that the XIST expressions of cardiomyocyte line, H9c2 were apparently suppressed by long-time hypoxia exposure under low glucose supply. On the contrary, miRNA-125b showed reverse expression pattern to XIST. We identified that XIST functioned as a ceRNA of miR-125b to downregulate its expression in both cell line and rat primary cardiomyocyte. Under low glucose supply, H9c2 cells exhibited increased susceptibility to hypoxia. We observed overexpression of XIST significantly elevated glycose metabolism rate under hypoxia, but overexpression of miR-125b inhibited glycose metabolism rate of cardiomyocyte under hypoxia. The glycolysis enzyme, hexokinase 2 (HK2) was validated as a direct target of miR-125b, which binds to the 3'-UTR region of HK2 mRNA in cardiomyocytes. Moreover, inhibition of miR-125b significantly protected the hypoxia-induced cardiomyocyte injury through restoration of glucose metabolism. Finally, we demonstrated that transfection of miR-125b in lncRNA-XIST overexpressed H9c2 cells effectively abolished the XIST-activated glucose metabolism and cardiomyocyte protection under hypoxia. The present study illustrates roles of the XIST-miR-125b-HK2 axis in the hypoxia-induced cardiomyocyte injury and proposes that maintaining glucose metabolism might be an effective approach for protection of cardiomyocyte injury.

Xiao-Qing-Long-Tang Maintains Cardiac Function during Heart Failure with Reduced Ejection Fraction in Salt-Sensitive Rats by Regulating the Imbalance of Cardiac Sympathetic Innervation.

OBJECTIVE: The anatomical and functional imbalances of sympathetic nerves are associated with cardiovascular disease progression. Xiao-Qing-Long-Tang (XQLT), an ancient Chinese herbal formula, has been used to treat cardiovascular diseases in eastern Asia for thousands of years. We determined the effect of XQLT in maintaining cardiac function during heart failure with reduced ejection fraction (HFrEF) with respect to its neurobiological effects in salt-sensitive rats. METHODS: Dahl salt-sensitive (DS) rats were fed a high-salt diet to establish an HFrEF model and were divided into model (DS, administered normal saline) and XQL groups (administrated XQLT) randomly, with SS-13BN rats being used as the control. The bodyweight and blood pressure of rats were observed regularly. Electrocardiogram, echocardiography, and plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) were determined to assess cardiac function. The sympathetic tune and myocardial morphological changes were evaluated. Western blot and qRT-PCR were used to assay the expression of the nerve growth factor (NGF) and leukemia inhibitory factor (LIF). Tyrosine hydroxylase (TH), choline acetyltransferase (CHAT), and growth-associated protein 43 (GAP43) were assayed to confirm sympathetic remodeling. The micromorphological changes in cardiac sympathetic nerve endings were observed by transmission electron microscopy. RESULTS: Four weeks after XQLT treatment, cardiac function and bodyweight were higher and blood pressure was lower than that of the DS group. Myocardial noradrenaline (NA) increased, while the plasma NA level decreased significantly. The morphology demonstrated that XQLT significantly alleviated myocardial damage. XQLT decreased the expression of LIF, increased the expression of NGF, enhanced the TH+/GAP43+ and TH+/CHAT + positive nerve fiber density, and improved the TH and GAP43 protein expression, but had no effect on CHAT. Moreover, XQLT improved the micromorphology of sympathetic nerve endings in the myocardium. CONCLUSION: XQLT maintains cardiac function during HFrEF in salt-sensitive rats, in part, by regulating the imbalance of cardiac sympathetic innervation.

Structural determinants for the interactions between muscarinic toxin 7 and muscarinic acetylcholine receptors.

Muscarinic acetylcholine receptors (mAChRs) have five subtypes and play crucial roles in various physiological functions and pathophysiological processes. Poor subtype specificity of mAChR modulators has been an obstacle to discover new therapeutic agents. Muscarinic toxin 7 (MT7) is a natural peptide toxin with high selectivity for the M1 receptor. With three to five residues substituted, M3, M4, and M5 receptor mutants could bind to MT7 at nanomolar concentration as the M1 receptor. However, the structural mechanisms explaining MT7-mAChRs binding are still largely unknown. In this study, we constructed 10 complex models of MT7 and each mAChR subtype or its mutant, performed molecular dynamics simulations, and calculated the binding energies to investigate the mechanisms. Our results suggested that the structural determinants for the interactions on mAChRs were composed of some critical residues located separately in the extracellular loops of mAChRs, such as Glu4.56, Leu4.60, Glu/Gln4.63, Tyr4.65, Glu/Asp6.67, and Trp7.35. The subtype specificity of MT7 was attributed to the non-conserved residues at positions 4.56 and 6.67. These structural mechanisms could facilitate the discovery of novel mAChR modulators with high subtype specificity and enhance the understanding of the interactions between ligands and G-protein-coupled receptors.

Determination of Meserine, a new candidate for Alzheimer's disease in mice brain by liquid chromatography-tandem mass spectrometry and its application to a pharmacokinetic and tissue distribution study.

A rapid and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for determination of Meserine ((-)-meptazinol phenylcarbamate), a novel potent inhibitor of acetylcholinesterase (AChE), was developed, validated, and applied to a pharmacokinetic study in mice brain. The lower limit of quantification (LLOQ) was 1 ng mL(-1) and the linear range was 1-1,000 ng mL(-1). The analyte was eluted on a Zorbax SB-Aq column (2.1 × 100 mm, 3.5 µm) with the mobile phase composed of methanol and water (70:30, v/v, aqueous phase contained 10 mM ammonium formate and 0.3% formic acid) using isocratic elution, and monitored by positive electrospray ionization in multiple reaction monitoring (MRM) mode. The flow rate was 0.25 mL min(-1). The injection volume was 5 µL and total run time was 4 min. The relative standard deviation (RSD) of intraday and interday variation was 2.49-7.81 and 3.01-7.67%, respectively. All analytes were stable after 4 h at room temperature and 6 h in autosampler. The extraction recoveries of Meserine in brain homogenate were over 90%. The main brain pharmacokinetic parameters obtained after intranasal administration were T max = 0.05 h, C max = 462.0 ± 39.7 ng g(-1), T 1/2 = 0.4 h, and AUC(0-∞) = 283.1 ± 9.1 ng h g(-1). Moreover, Meserine was distributed rapidly and widely into brain, heart, liver, spleen, lung, and kidney tissue. The method is validated and could be applied to the pharmacokinetic and tissue distribution study of Meserine in mice.