Application of microbial enhanced oil recovery technique to a Turkish heavy oil

Summary Microbial enhance oil recovery utilizes microorganisms and their metabolic products to improve the recovery of crude oil from reservoir rocks. In this study an anaerobic bacterium, Clostridium acetobutylicum was injected into a one-dimensional model reservoir containing a Turkish heavy oil (Raman oil) at 38° C. This injection was followed by water flooding after a suitable shut-in period. Comparison of oil recovery results of pure water flooding runs with experiments in which bacterial concentration and shut-in periods were varied indicated increases in oil recovery of about 12% of the original oil in place. This increase was attributed to changes in the viscosity and pH of the crude oil.Offprint requests to: T. Mehmetoglu     

Automated identification of diseases related to lymph system from lymphography data using artificial immune recognition system with fuzzy resource allocation mechanism (fuzzy-AIRS)

Artificial immune recognition system (AIRS) classification algorithm, which has an important place among classification algorithms in the field of artificial immune systems, has showed an effective and intriguing performance on the problems it was applied. AIRS was previously applied to some medical classification problems including breast cancer, Cleveland heart disease, diabetes and it obtained very satisfactory results. So, AIRS proved to be an efficient artificial intelligence technique in medical field. In this study, the resource allocation mechanism of AIRS was changed with a new one determined by fuzzy-logic. This system, named as fuzzy-AIRS was used as a classifier in the diagnosis of lymph diseases, which is of great importance in medicine. The classifications of lymph diseases dataset taken from University of California at Irvine (UCI) Machine Learning Repository were done using 10-fold cross-validation method. Reached classification accuracies were evaluated by comparing them with reported classifiers in UCI web site in addition to other systems that are applied to the related problems. Also, the obtained classification performances were compared with AIRS with regard to the classification accuracy, number of resources and classification time. While only AIRS algorithm obtained 83.138% classification accuracy, fuzzy-AIRS classified the lymph diseases dataset with 90.00% accuracy. For lymph diseases dataset, fuzzy-AIRS obtained the highest classification accuracy according to the UCI web site. Beside of this success, fuzzy-AIRS gained an important advantage over the AIRS by means of classification time. By reducing classification time as well as obtaining high classification accuracies in the applied datasets, fuzzy-AIRS classifier proved that it could be used as an effective classifier for medical problems.     

Isolation and characterization of long-chain alkane–degrading Acinetobacter sp. BT1A from oil-contaminated soil in Diyarbakır,in the Southeast of Turkey

A strain of long-chain alkane–degrading bacteria, BT1A, was isolated from oil-contaminated soil in Diyarbak?r, in the southeast of Turkey. Morphological, biochemical, and physiological characterization and 16S rRNA gene sequence analysis showed that the strain BT1A was a member of Acinetobacter genus, and it was found to be closely related to Acinetobacter baumannii. The strain BT1A was able to utilize crude petroleum as carbon and energy sources in order to grow. Among the aliphatic hydrocarbons, growth was observed only in the medium containing long-chain alkanes (tridecane, pentadecane, and hexadecane) and squalene. Hexadecane was the most preferred hydrocarbon among the long-chain alkanes. Gas chromatography–mass spectrometry (GC-MS) analysis showed that BT1A degraded 83% of n-alkanes of 1% crude oil in 7 days. The present study indicates that the isolated strain can well be used for biodegradation of hydrocarbons in oil-contaminated sites.     

Activation of ERK by Ca2+ store depletion in rat liver epithelial cells

In rat liver epithelial (WB) cells,Ca²⁺ pool depletion induced by twoindependent methods resulted in activation of extracellular signal-regulated protein kinase (ERK). In the first method,Ca²⁺ pool depletion bythapsigargin increased the activity of ERK, even when rise in cytosolicCa²⁺ was blocked with theCa²⁺ chelator BAPTA-AM. For thesecond method, addition of extracellular EGTA at a concentration shownto deplete intracellular Ca²⁺pools also increased ERK activity. In each instance, ERK activation, asmeasured by an immunocomplex kinase assay, was greatly reduced by thetyrosine kinase inhibitor genistein, suggesting thatCa²⁺ store depletion increased ERKactivity through a tyrosine kinase pathway. The intracellularCa²⁺-releasing agent thapsigarginincreased Fyn activity, which was unaffected by BAPTA-AM pretreatment,suggesting that Fyn activity was unaffected by increased cytosolic freeCa²⁺. Furthermore, depletion ofintracellular Ca²⁺ with EGTAcaused inactivation of protein phosphatase 2A and protein tyrosinephosphatases. ANG II-induced activations of Fyn, Raf-1, and ERK wereaugmented in cells pretreated with BAPTA-AM, but ANG II-inducedexpression of the dual-specificity phosphatase mitogen-activatedprotein kinase phosphatase-1 was blocked by BAPTA-AM pretreatment.Together these results indicate that ERK activity is regulated by thebalance of phosphorylation vs. dephosphorylation reactions in intactcells and that the amount of Ca²⁺stored in intracellular pools plays an important role in this regulation.

     

Novel benzimidazole derivatives as selective CB2 agonists

The preparation and evaluation of a novel class of CB2 agonists based on a benzimidazole moiety are reported. They showed binding affinities up to 1nM towards the CB2 receptor with partial to full agonist potencies. They also demonstrated good to excellent selectivity (>1000-fold) over the CB1 receptor.     

Serum and Cerebrospinal Fluid Magnesium Levels, Glasgow Coma Scores, and In-Hospital Mortality in Patients with Acute Stroke

The aim of this study was to determine the relationship between serum and cerebrospinal fluid (CSF) magnesium (Mg⁺²) levels, Glasgow Coma Scores (GCS), and 7-day mortality in acute stroke patients. Patients with acute ischemic or hemorrhagic stroke arriving within the first 3 h of symptoms were included in the study. The control group consisted of healthy volunteers. GCS was determined, and blood and CSF samples were taken in order to establish serum and CSF glucose, Mg⁺², sodium, potassium, calcium, and chlorine levels. Mortality was recorded at 7 days after admission. CSF Mg⁺² in the ischemic infarct group was significantly lower than in the control group (p = 0.006). CSF Mg⁺² in the ischemic infarct patients with a GCS ≤ 8 were significantly lower (p = 0.002) than controls and in ischemic infarct patients with a GCS ≥9. In the ischemic stroke patients, CSF Mg⁺² and GCS were significantly correlated (r = 55, p = 0.031). CSF Mg⁺² levels in ischemic stroke patients who died within 7 days were significantly lower than controls, ischemic stroke patients who survived, and hemorrhagic stroke patients who died (p = 0.002, p = 0.042, and p = 0.005, respectively). Low CSF Mg⁺² levels in patients with acute ischemic stoke at admission predicted a higher 1-week mortality.