Anticancer activity of Araguspongine C via inducing apoptosis, and inhibition of oxidative stress, inflammation, and EGFR-TK in human lung cancer cells: An in vitro and in vivo study.

The advanced non-small cell lung cancer (NSCLC) that harbors epidermal growth factor receptor (EGFR) mutations has put a selective pressure on the discovery and development of newer EGFR inhibitors. Therefore, the present study intends to explore the pharmacological effect of Araguspongine C (Aragus-C) as anticancer agent against lung cancer. The effect of Aragus-C was evaluated on the viability of the A549 and H1975 cells. Further biochemical assays were performed to elaborate the effect of Aragus-C, on the apoptosis, cell-cycle analysis, and mitochondrial membrane potential in A549 cells. Western blot analysis was also conducted to determine the expression of EGFR in A549 cells. Tumor xenograft mice model from A549 cells was established to further elaborate the pharmacological activity of Aragus-C. Results suggest that Aragus C showed significant inhibitory activity against A549 cells as compared to H1975 cells. It has been found that Aragus-C causes the induction of apoptosis and promotes cell-cycle arrest at the G2/M phase of A549 cells. It also showed a reduction in the overexpression of EGFR in A549 cells. In tumor xenograft mice model, it showed a significant reduction of tumor volume in a dose-dependent manner, with maximum inhibitory activity was reported by the 8 mg/kg treated group. It also showed significant anti-inflammatory and antioxidant activity by reducing the level of TNF-α, IL-1ß, IL-6, and MDA, with a simultaneous increase of superoxide dismutase and glutathione peroxidase. We have demonstrated the potent anti-lung cancer activity of Aragus-C, and it may be considered as a potential therapeutic choice for NSCLC treatment.

Powerful molecule generation with simple ConvNet.

MOTIVATION: Automated molecule generation is a crucial step in in-silico drug discovery. Graph-based generation algorithms have seen significant progress over recent years. However, they are often complex to implement, hard to train and can under-perform when generating long-sequence molecules. The development of a simple and powerful alternative can help improve practicality of automated drug discovery method. RESULTS: We proposed a ConvNet-based sequential graph generation algorithm. The molecular graph generation problem is reformulated as a sequence of simple classification tasks. At each step, a convolutional neural network operates on a sub-graph that is generated at previous step, and predicts/classifies an atom/bond adding action to populate the input sub-graph. The proposed model is pretrained by learning to sequentially reconstruct existing molecules. The pretrained model is abbreviated as SEEM (structural encoder for engineering molecules). It is then fine-tuned with reinforcement learning to generate molecules with improved properties. The fine-tuned model is named SEED (structural encoder for engineering drug-like-molecules). The proposed models have demonstrated competitive performance comparing to 16 state-of-the-art baselines on three benchmark datasets. AVAILABILITY AND IMPLEMENTATION: Code is available at https://github.com/yuh8/SEEM and https://github.com/yuh8/SEED. QM9 dataset is availble at http://quantum-machine.org/datasets/, ZINC250k dataset is availble at https://raw.githubusercontent.com/aspuru-guzik-group/chemical_vae/master/models/zinc_properties/250k_rndm_zinc_drugs_clean_3.csv, and ChEMBL dataset is availble at https://www.ebi.ac.uk/chembl/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Ketotic cows display a different serum nonesterified fatty acid composition.

The experiments reported in this research communication aimed to compare the serum nonesterified fatty acid (NEFA) composition in ketotic cows and healthy cows during the perinatal period. NEFAs play significant roles in etiology and pathology of ketosis. We hypothesized that ketotic cows will display a different serum NEFA composition compared to healthy controls, and fatty acid related indicators for ketosis prediction can be screened. Pre-partum healthy cows were recruited, and blood samples were collected on -7, 3, 7, 14 and 21 d postpartum. Cows were further divided into a healthy control group (C group, n = 6) and a ketosis group (K group, n = 6) if blood ß-hydroxybutyric acid levels exceeded 1.2 mm during the experiment. NEFA composition was then analyzed by means of Gas Chromatography-Mass Spectrometer (GC-MS). Only C12 : 0% was significantly higher in C group than K group on 7 d pre-partum (P < 0.05), when the cows were not diagnosed with ketosis. Five fatty acids displayed statistical differences in composition between C and K group (P < 0.05), namely C12 : 0, C16 : 0, C17 : 0, C18 : 1n9 and C22 : 1n9. Saturates%, unsaturates%, mono-unsaturates% and saturates/unsaturates were also different between C and K group (P < 0.05). Of note, C18 : 1n9/C12 : 0 and C18 : 1n9/C22 : 1n9 in K group were significantly higher than those in controls on 7 d pre-partum (P < 0.05). It is suggested that the ratios show potential as indicators for prediction of ketosis.

Significant changes in ITIH4, AHSG, ORM1, and CD46 content in milk fat globule membrane proteins of ketotic dairy cows.

High concentrations of non-esterified fatty acid (NEFA) and ß-hydroxybutyrate (BHBA) in cows' blood caused by ketosis are associated with inflammatory states. We hypothesised that ketosis in postparturient dairy cows would result in altered levels on inflammation-related proteins not only in plasma but also in the milk fat globule membranes (MFGM). Thirty cows were selected from a dairy farm in Heilongjiang, China. Inflammatory milk fat globule membrane proteins were detected using ELISA kits, and a fully automatic biochemical analyser was used to measure the concentrations of BHBA, NEFA, glucose (GLU) and triglyceride (TG) in plasma. MFGM protein from milk of ketotic cows contained significantly different concentrations of acute-phase response proteins (complement C3 (C3), prothrombin (F2), alpha-1-acid glycoprotein (ORM1), inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), alpha-2-HS-glycoprotein (AHSG), complement C9 (C9), complement regulatory protein variant 4 (CD46)) in comparison with milk from non-ketotic cows. Blood concentrations of C3, complement C9 (C9), tumour necrosis factor α (TNFα), MFGM C3, monocyte differentiation antigen CD14 (CD14) and ORM1 levels were correlated with energy balance. ITIH4 and CD46 increased, and AHSG and ORM1 decreased before the onset of ketosis. These biomarkers offer potential as predictors and monitors of ketosis in at-risk cows.

FGF-21: promising biomarker for detecting ketosis in dairy cows.

The objective of this study was to investigate the measurement of serum fibroblast growth factor-21 (FGF-21), a protein mainly synthesized by the liver, as a sensitive biomarker for diagnosis of ketosis in dairy cows. Ninety Holstein-Friesian dairy cows (60 healthy and 30 ketosis cases) were selected and divided into a Ketosis group (K), and a Control group (C). We measured serum FGF-21 and other biochemical parameters by commercial ELISA kits. In a combined population of all 90 cows, we found that serum FGF-21 level was lower (P < 0.001) in cows suffering from ketosis. When the ß-hydroxybutyric acid (BHBA) level increased over 1.2 mmol/L, the FGF-21 level tended to decline below 300.85 pg/ml. The area under the receiver operating characteristic curve (AUC-ROC) for serum FGF-21 for diagnosis of fatty liver was 0.952-0.025 [95% confidence interval (CI) 0.904, 1.000] which was higher than the AUC-ROC for glucose (Glc) and other tested parameters. We concluded that FGF-21 could be a diagnostic parameter in the evaluation and auxiliary diagnosis of changes in the energy metabolism state, and serum FGF-21 measurement would have a considerable clinical impact and lead to greater profitability in the dairy industry.

The relationship between Fibroblast Growth Factor-21 and characteristic parameters related to energy balance in dairy cows.

BACKGROUND: Negative energy balance (NEB) is a common pathological foundation of ketosis and fatty liver. Liver and fat tissue are the major organs of lipid metabolism and take part in modulating lipid oxidative capacity and energy demands, which is also a key metabolic pathway that regulates NEB develop during perinatal period. Fibroblast growth factor-21 (FGF-21) is a recently discovered protein hormone that plays an important and specific regulating role in adipose lipid metabolism and liver gluconeogenesis for human and mouse. Our aim is to investigate the variation and relationship between serum FGF-21 concentration and characteristic parameters related to negative energy balance in different energy metabolism state. METHODS: In this research, five non-pregnant, non-lactating Holstein-Friesian dairy cows were randomly allocated into two groups. The interventions were a controlled-energy diet (30% of maintenance energy requirements) and a moderate-energy diet (120% of predicted energy requirements) that lasted for the duration of the experiment. We measured biochemical parameters, serum FGF-21, leptin and insulin levels by commercial ELISA kits. RESULTS: The results showed that serum FGF-21 levels were significantly higher in both groups treated with a controlled-energy diet, while FGF-21 levels in both groups treated with moderate-energy diet were low. FGF-21 levels exhibited a significant positive correlation with serum leptin levels, while an inverse relationship was found between FGF-21 and blood glucose and ß-hydroxybutyrate acid (BHBA) levels. CONCLUSION: An increase in FGF-21 levels after a controlled-energy diet treatment may contribute to a positive metabolic effect which could result in a new theoretical and practical basis for the preventive strategy of dairy cows with NEB.

[Rapid screening and confirmation of antidepressants in blood using automated solid phase extraction and liquid chromatography-time-of-flight mass spectrometry].

A high-throughput method was developed for screening antidepressants in blood by automated solid phase extraction and liquid chromatography with high resolution quadrupole-time-of-flight mass spectrometry (ASPE-LC-Q-TOF/MS). The samples were cleaned up by an HLB solid phase extraction cartridge and analyzed by LC-Q-TOF/MS under electrospray ionization (ESI) mode with scanning range of m/z 50-1 000 Da. The chromatographic separation was performed on an Agilent Eclipse Plus C18 column (50 mm x 2.1 mm, 1.8 microm) with gradient elution using methanol and 5 mmol/L ammonium formate aqueous solution (containing 0.2% formic acid) as mobile phases. Rapid screening and confirmation can be achieved using MS matching scores, deviation of retention time, measured mass, isotopic abundance matching scores, isotope space matching scores and MS/MS matching scores. The quantitative analysis was carried out by correlating the extracting peak area with accurate mass. Good linearities were observed in the range of 1 - 500 microg/L with the correlation coefficients from 0.997 6 to 0.999 7. The limits of detection were 0.01-0.5 microg/L. The spiked recoveries were 79.6%-96.4% with the relative standard deviations of 4.1% - 6.4%. The result screening database was built using Agilent MassHunter PCDL Manager software and then used for the analysis of spiked samples. MS matching scores, isotopic abundance matching scores, isotope space matching scores (all > 95 points) and MS/MS matching scores (> 70 points) were applied to identify the analytes. The results showed that all the spiked antidepressants could be correctly identified with low deviation of retention time (< 0.1 min) and mass (< 1 mDa). The developed method was further applied for the analysis of poisoning cases, and amitriptyline, carbamazepine, doxepin were detected. In brief, the method is rapid, sensitive, simple, reliable, and suitable for the screening and confirmation of antidepressants in forensic and clinical analytical toxicology.

Associations of PLA2G7 gene polymorphisms with plasma lipoprotein-associated phospholipase A2 activity and coronary heart disease in a Chinese Han population: the Beijing atherosclerosis study.

The human PLA2G7 gene encodes lipoprotein-associated phospholipase A(2) (Lp-PLA(2)), an emerging risk factor for cardiovascular diseases. In the present study, seven single nucleotide polymorphisms (SNPs) in the PLA2G7 gene were genotyped in 827 patients with coronary heart disease (CHD), of which 512 were patients with myocardial infarction (MI), and 947 age- and gender-matched controls in a Chinese Han population. Plasma Lp-PLA(2) activity was measured in 416 randomly selected controls and 689 randomly selected CHD patients, including 423 MI patients. Lp-PLA(2) activity in CHD and MI cases was significantly higher (233.42+/-57.66 and 234.27+/-59.51 nmol ml(-1) min(-1), respectively) than in controls (211.47+/-58.61 nmol ml(-1) min(-1)). After adjusting for traditional risk factors by logistic regression, the odds ratios for CHD and MI per 1 standard deviation increment of Lp-PLA(2) activity were 1.27 (95% CI, 1.07-1.50) and 1.27 (95% CI, 1.05-1.54), respectively. Both single SNP analysis and haplotype analysis showed that the V279F and I198T polymorphisms were significantly associated with the reduced Lp-PLA(2) activity, but neither was associated with increased CHD risk. Both univariate and multivariate analyses, adjusting effects of conventional factors, indicated that the rs13210554 T allele increased the risk of MI in this Chinese Han population. In summary, an independent association of increased plasma Lp-PLA(2) activity with CHD and MI existed in this Chinese Han Population. Although V279F and I198T mutations significantly decreased the activity of Lp-PLA(2), only the promoter rs13210554 polymorphism was associated with MI. Lp-PLA(2) activity appears to influence the CHD and MI risk in Chinese Han population.

Influence of fibrinogen beta-chain gene variations on risk of myocardial infarction in a Chinese Han population.

BACKGROUND: Although the role of fibrinogen as a predictor of acute myocardial infarction (MI) has been well-established, the association of genetic polymorphisms in the fibrinogen gene with MI is still controversial. This study was conducted to elucidate the association between the genetic polymorphisms of the fibrinogen beta-chain (FGB) gene and MI in Chinese Han population. METHODS: The occurrence of 3 common polymorphisms (i.e., -455G/A, R448K and 8558C/G) in a case-control study including 508 patients with MI and 503 healthy controls was investigated. Results Analyses of single polymorphisms showed that individuals carrying the rare alleles for the 3 polymorphisms were significantly associated with a decreased risk of MI. Logistic regression analysis indicated that R448K remained independently associated with MI after adjustment for environmental risk factors (adjusted odds ratio(OR) = 0.71 for KK/RK versus RR, P = 0.023). The three polymorphisms were found to be in strong linkage disequilibrium. Haplotype analyses showed that the A-K-G haplotype (-455A, 448K, 8558G) was associated with a protective effect against MI. Compared with the common haplotype G-R-C, the adjusted OR for A-K-G was 0.68 (95% CI, 0.51-0.90; P = 0.006). CONCLUSION: These data indicate that individuals carrying the FGB 448K allele may be protective against having MI in this population.