Enzyme classification with peptide programs: a comparative study

<p>Abstract</p> <p>Background</p> <p>Efficient and accurate prediction of protein function from sequence is one of the standing problems in Biology. The generalised use of sequence alignments for inferring function promotes the propagation of errors, and there are limits to its applicability. Several machine learning methods have been applied to predict protein function, but they lose much of the information encoded by protein sequences because they need to transform them to obtain data of fixed length.</p> <p>Results</p> <p>We have developed a machine learning methodology, called peptide programs (PPs), to deal directly with protein sequences and compared its performance with that of Support Vector Machines (SVMs) and BLAST in detailed enzyme classification tasks. Overall, the PPs and SVMs had a similar performance in terms of Matthews Correlation Coefficient, but the PPs had generally a higher precision. BLAST performed globally better than both methodologies, but the PPs had better results than BLAST and SVMs for the smaller datasets.</p> <p>Conclusion</p> <p>The higher precision of the PPs in comparison to the SVMs suggests that dealing with sequences is advantageous for detailed protein classification, as precision is essential to avoid annotation errors. The fact that the PPs performed better than BLAST for the smaller datasets demonstrates the potential of the methodology, but the drop in performance observed for the larger datasets indicates that further development is required.</p> <p>Possible strategies to address this issue include partitioning the datasets into smaller subsets and training individual PPs for each subset, or training several PPs for each dataset and combining them using a bagging strategy.</p

American ginseng suppresses Western diet-promoted tumorigenesis in model of inflammation-associated colon cancer: role of EGFR

<p>Abstract</p> <p>Background</p> <p>Western diets increase colon cancer risk. Epidemiological evidence and experimental studies suggest that ginseng can inhibit colon cancer development. In this study we asked if ginseng could inhibit Western diet (20% fat) promoted colonic tumorigenesis and if compound K, a microbial metabolite of ginseng could suppress colon cancer xenograft growth.</p> <p>Methods</p> <p>Mice were initiated with azoxymethane (AOM) and, two weeks later fed a Western diet (WD, 20% fat) alone, or WD supplemented with 250-ppm ginseng. After 1 wk, mice received 2.5% dextran sulfate sodium (DSS) for 5 days and were sacrificed 12 wks after AOM. Tumors were harvested and cell proliferation measured by Ki67 staining and apoptosis by TUNEL assay. Levels of EGF-related signaling molecules and apoptosis regulators were determined by Western blotting. Anti-tumor effects of intraperitoneal compound K were examined using a tumor xenograft model and compound K absorption measured following oral ginseng gavage by UPLC-mass spectrometry. Effects of dietary ginseng on microbial diversity were measured by analysis of bacterial 16S rRNA.</p> <p>Results</p> <p>Ginseng significantly inhibited colonic inflammation and tumorigenesis and concomitantly reduced proliferation and increased apoptosis. The EGFR cascade was up-regulated in colonic tumors and ginseng significantly reduced EGFR and ErbB2 activation and Cox-2 expression. Dietary ginseng altered colonic microbial diversity, and bacterial suppression with metronidazole reduced serum compound K following ginseng gavage. Furthermore, compound K significantly inhibited tumor xenograft growth.</p> <p>Conclusions</p> <p>Ginseng inhibited colonic inflammation and tumorigenesis promoted by Western diet. We speculate that the ginseng metabolite compound K contributes to the chemopreventive effects of this agent in colonic tumorigenesis.</p

Cardiovascular Outcomes in Acute Coronary Syndrome and Malnutrition: A Meta-Analysis of Nutritional Assessment Tools

Background: There is emerging evidence that malnutrition is associated with poor prognosis among patients with acute coronary syndrome (ACS). // Objectives: This study seeks to elucidate the prognostic impact of malnutrition in patients with ACS and provide a quantitative review of most commonly used nutritional assessment tools. // Methods: Medline and Embase were searched for studies reporting outcomes in patients with malnutrition and ACS. Nutritional screening tools of interest included the Prognostic Nutrition Index, Geriatric Nutritional Risk Index, and Controlling Nutritional Status. A comparative meta-analysis was used to estimate the risk of all-cause mortality and cardiovascular events based on the presence of malnutrition and stratified according to ACS type, ACS intervention, ethnicity, and income. // Results: Thirty studies comprising 37,303 patients with ACS were included, of whom 33.5% had malnutrition. In the population with malnutrition, the pooled mortality rate was 20.59% (95% CI: 14.95%-27.67%). Malnutrition was significantly associated with all-cause mortality risk after adjusting for confounders including age and left ventricular ejection fraction (adjusted HR: 2.66, 95% CI: 1.78-3.96, P = 0.004). There was excess mortality in the group with malnutrition regardless of ACS type (P = 0.132), ethnicity (P = 0.245), and income status (P = 0.058). Subgroup analysis demonstrated no statistically significant difference in mortality risk between individuals with and without malnutrition (P = 0.499) when using Controlling Nutritional Status (OR: 7.80, 95% CI: 2.17-28.07, P = 0.011), Geriatric Nutritional Risk Index (OR: 4.30, 95% CI: 2.78-6.66, P < 0.001), and Prognostic Nutrition Index (OR: 4.67, 95% CI: 2.38-9.17, P = 0.023). // Conclusions: Malnutrition was significantly associated with all-cause mortality risk following ACS, regardless of ACS type, ethnicity, and income status, underscoring the importance of screening and interventional strategies for patients with malnutrition

Prediction of potential drug targets based on simple sequence properties

<p>Abstract</p> <p>Background</p> <p>During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets.</p> <p>Results</p> <p>Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research.</p> <p>Conclusion</p> <p>We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.</p

Observation of a ppb mass threshoud enhancement in \psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p}) decay

The decay channel $\psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p})$ is studied using a sample of $1.06\times 10^8$ $\psi^\prime$ events collected by the BESIII experiment at BEPCII. A strong enhancement at threshold is observed in the $p\bar{p}$ invariant mass spectrum. The enhancement can be fit with an $S$-wave Breit-Wigner resonance function with a resulting peak mass of $M=1861^{+6}_{-13} {\rm (stat)}^{+7}_{-26} {\rm (syst)} {\rm MeV/}c^2$ and a narrow width that is $\Gamma<38 {\rm MeV/}c^2$ at the 90% confidence level. These results are consistent with published BESII results. These mass and width values do not match with those of any known meson resonance.Comment: 5 pages, 3 figures, submitted to Chinese Physics

Suppression of MMP-9 by doxycycline in brain arteriovenous malformations

BACKGROUND: The primary aim of this study is to demonstrate the feasibility of utilizing doxycycline to suppress matrix metalloproteinase-9 (MMP-9) in brain arteriovenous malformations (AVMs). METHODS: Ex-vivo treatment of AVM tissues: Intact AVM tissues were treated with doxycycline for 48 hours. Active and total MMP-9 in the medium were measured. Pilot trial: AVM patients received either doxycycline (100 mg) or placebo twice a day for one week prior to AVM resection. Active and total MMP-9 in BVM tissues were measured. RESULTS: Ex-vivo treatment of AVM tissues: Doxycycline at 10 and 100 μg/ml significantly decreased MMP-9 levels in AVM tissues ex-vivo (total: control vs 10 vs 100 μg/ml = 100 ± 6 vs 60 ± 16 vs 61 ± 9%; active: 100 ± 8 vs 48 ± 16 vs 59 ± 10%). Pilot trial: 10 patients received doxycycline, and 4 patients received placebo. There was a trend for both MMP-9 levels to be lower in the doxycycline group than in the placebo group (total: 2.18 ± 1.94 vs 3.26 ± 3.58, P = .50; active: 0.48 ± 0.48 vs 0.95 ± 1.01 ng/100 μg protein, P = .25). CONCLUSIONS: A clinically relevant concentration of doxycycline decreased MMP-9 in ex-vivo AVM tissues. Furthermore, there was a trend that oral doxycycline for as short as one week resulted in a decrease in MMP-9 in AVM tissues. Further studies are warranted to justify a clinical trial to test effects of doxycycline on MMP-9 expression in AVM tissues

Multi-scale spatio-temporal analysis of human mobility

The recent availability of digital traces generated by phone calls and online logins has significantly increased the scientific understanding of human mobility. Until now, however, limited data resolution and coverage have hindered a coherent description of human displacements across different spatial and temporal scales. Here, we characterise mobility behaviour across several orders of magnitude by analysing ∼850 individuals' digital traces sampled every ∼16 seconds for 25 months with ∼10 meters spatial resolution. We show that the distributions of distances and waiting times between consecutive locations are best described by log-normal and gamma distributions, respectively, and that natural time-scales emerge from the regularity of human mobility. We point out that log-normal distributions also characterise the patterns of discovery of new places, implying that they are not a simple consequence of the routine of modern life

Baicalin administration attenuates hyperglycemia-induced malformation of cardiovascular system

In this study, the effects of Baicalin on the hyperglycemia-induced cardiovascular malformation during embryo development were investigated. Using early chick embryos, an optimal concentration of Baicalin (6 μM), was identified which could prevent hyperglycemia-induced cardiovascular malformation of embryos. Hyperglycemia-enhanced cell apoptosis was reduced in embryos and HUVECs in the presence of Baicalin. Hyperglycemia-induced excessive ROS production was inhibited when Baicalin was administered. Analyses of SOD, GSH-Px, MAQE and GABAA suggested Baicalin plays an antioxidant role in chick embryos possibly through suppression of outwardly rectifying Cl(-) in the high-glucose microenvironment. In addition, hyperglycemia-enhanced autophagy fell in the presence of Baicalin, through affecting the ubiquitin of p62 and accelerating autophagy flux. Both Baicalin and Vitamin C could decrease apoptosis, but CQ did not, suggesting autophagy to be a protective function on the cell survival. In mice, Baicalin reduced the elevated blood glucose level caused by streptozotocin (STZ). Taken together, these data suggest that hyperglycemia-induced embryonic cardiovascular malformation can be attenuated by Baicalin administration through suppressing the excessive production of ROS and autophagy. Baicalin could be a potential candidate drug for women suffering from gestational diabetes mellitus

Increased Diacylglycerols Characterize Hepatic Lipid Changes in Progression of Human Nonalcoholic Fatty Liver Disease; Comparison to a Murine Model

The spectrum of nonalcoholic fatty liver disease (NAFLD) includes steatosis, nonalcoholic steatohepatitis (NASH), and progression to cirrhosis. While differences in liver lipids between disease states have been reported, precise composition of phospholipids and diacylglycerols (DAG) at a lipid species level has not been previously described. The goal of this study was to characterize changes in lipid species through progression of human NAFLD using advanced lipidomic technology and compare this with a murine model of early and advanced NAFLD.Utilizing mass spectrometry lipidomics, over 250 phospholipid and diacylglycerol species (DAGs) were identified in normal and diseased human and murine liver extracts.Significant differences between phospholipid composition of normal and diseased livers were demonstrated, notably among DAG species, consistent with previous reports that DAG transferases are involved in the progression of NAFLD and liver fibrosis. In addition, a novel phospholipid species (ether linked phosphatidylinositol) was identified in human cirrhotic liver extracts.Using parallel lipidomics analysis of murine and human liver tissues it was determined that mice maintained on a high-fat diet provide a reproducible model of NAFLD in regards to specificity of lipid species in the liver. These studies demonstrated that novel lipid species may serve as markers of advanced liver disease and importantly, marked increases in DAG species are a hallmark of NAFLD. Elevated DAGs may contribute to altered triglyceride, phosphatidylcholine (PC), and phosphatidylethanolamine (PE) levels characteristic of the disease and specific DAG species might be important lipid signaling molecules in the progression of NAFLD