Molecular follow-up of disease progression and interferon therapy in chronic myelocytic leukemia

We previously reported that the abl promoter (Pa) undergoes de novo DNA methylation in the course of chronic myelocytic leukemia (CML). The clinical implications of this finding are the subject of the present study in which samples of CML patients, including a group treated with interferon alpha (IFNalpha) were surveyed. The methylation status of the abl promoter was monitored by polymerase chain reaction (PCR) amplification of the Pa region after digestion with several site-methylation sensitive restriction enzymes. Some 74% of the DNA samples from blood and marrow drawn in the chronic phase were nonmethylated, similar to control samples from non-CML patients. The remaining 26% were partially methylated in the abl Pa region. The latter samples were derived from patients who were indistinguishable from the others on the basis of clinical presentation. Methylated samples were mostly derived from patients known to have a disease of longer duration (26 months v 7.5 months, P = .01). Samples of 30 IFNalpha-treated patients were sequentially analyzed in the course of treatment. Fifteen patients with no evidence of Pa methylation before treatment remained methylation-free. The remainder, who displayed Pa methylation before treatment, reverted to the methylation-free status. The outcome is attributed to IFNalpha therapy, as the Pa methylation status was not reversed in any of the patients treated with hydroxyurea. Methylation of the abl promoter indicates a disease of long-standing, most likely associated with a higher probability of imminent blastic transformation. It appears to predict the outcome of IFNalpha therapy far better than the cytogenetic response.     

Simulation of Natural Depletion and Miscible Gas Injection Effects on Asphaltene Stability in Petroleum Reservoir Fluids

Natural depletion of petroleum reservoirs as well as gas injection for enhance oil recovery, are unavoidable processes in the oil industry. Foremost, prediction of the problems due to these two processes is very necessary and important. So many field and experimental experiences have shown that heavy organic depositions, especially asphaltene deposition, are principal results during these processes. Results of laboratory simulation of asphaltene deposition during the natural depletion of petroleum reservoirs and also during gas injection and enhanced oil recovery (EOR) processes are reported here. This is achieved through the design of a new experimental setup for the investigation of pressure and composition effects on asphaltene deposition in petroleum fluids at high pressure and high temperature conditions. In this work, asphaltene deposition during decreasing pressure, from pressures greater than reservoir pressure to pressures below the bubble point pressure (natural depletion) and also asphaltene deposition during natural gas injection in reservoir conditions, are studied for three samples—one recombined sample and two bottomhole samples. All of the obtained results from this work conform to theoretical and other experimental works.     

Bi-level fuzzy based advanced reservation of Cloud workflow applications on distributed Grid resources

The increasing demand on execution of large-scale Cloud workflow applications which need a robust and elastic computing infrastructure usually lead to the use of high-performance Grid computing clusters. As the owners of Cloud applications expect to fulfill the requested Quality of Services (QoS) by the Grid environment, an adaptive scheduling mechanism is needed which enables to distribute a large number of related tasks with different computational and communication demands on multi-cluster Grid computing environments. Addressing the problem of scheduling large-scale Cloud workflow applications onto multi-cluster Grid environment regarding the QoS constraints declared by application’s owner is the main contribution of this paper. Heterogeneity of resource types (service type) is one of the most important issues which significantly affect workflow scheduling in Grid environment. On the other hand, a Cloud application workflow is usually consisting of different tasks with the need for different resource types to complete which we call it heterogeneity in workflow. The main idea which forms the soul of all the algorithms and techniques introduced in this paper is to match the heterogeneity in Cloud application’s workflow to the heterogeneity in Grid clusters. To obtain this objective a new bi-level advanced reservation strategy is introduced, which is based upon the idea of first performing global scheduling and then conducting local scheduling. Global-scheduling is responsible to dynamically partition the received DAG into multiple sub-workflows that is realized by two collaborating algorithms: (1) The Critical Path Extraction algorithm (CPE) which proposes a new dynamic task overall critically value strategy based on DAG’s specification and requested resource type QoS status to determine the criticality of each task; and (2) The DAG Partitioning algorithm (DAGP) which introduces a novel dynamic score-based approach to extract sub-workflows based on critical paths by using a new Fuzzy Qualitative Value Calculation System to evaluate the environment. Local-scheduling is responsible for scheduling tasks on suitable resources by utilizing a new Multi-Criteria Advance Reservation algorithm (MCAR) which simultaneously meets high reliability and QoS expectations for scheduling distributed Cloud-base applications. We used the simulation to evaluate the performance of the proposed mechanism in comparison with four well-known approaches. The results show that the proposed algorithm outperforms other approaches in different QoS related terms.     

Non-Cytokine Protein Profile of the Mesenchymal Stem Cell Secretome That Regulates the Androgen Production Pathway

Polycystic ovary syndrome (PCOS) is the most common endocrine and metabolic disorder in reproductive-aged women, and it typically involves elevated androgen levels. Recently, it has been reported that human bone marrow mesenchymal stem cells (hBM-MSCs) can regulate androgen synthesis pathways. However, the details of the mechanism are still unclear. hBM-MSC-derived secreted factors (the secretome) are promising sources of cell-based therapy as they consist of various types of proteins. It is thus important to know which proteins interact with disease-implicated biomolecules. This work aimed to investigate which secretome components contain the key factor that inhibits testosterone synthesis. In this study, we fractionated hBM-MSC-conditioned media into three fractions based on their molecular weights and found that, of the three fractions, one had the ability to inhibit the androgen-producing genes efficiently. We also analyzed the components of this fraction and established a protein profile of the hBM-MSC secretome, which was shown to inhibit androgen synthesis. Our study describes a set of protein components present in the hBM-MSC secretome that can be used therapeutically to treat PCOS by regulating androgen production for the first time.     

Interactive effects of aging parameters of AA6056

The effect of thermomechanical treatment on the aging behavior of AA6056 aluminum alloy was modeled using response surface methodology (RSM). Two models were developed to predict the final yield stress (FYS) and elongation amounts as well as the optimum conditions of aging process. These were done based on the interactive effects of applied thermomechanical parameters. The optimum condition predicted by the model to attain the maximum strength was pre-aging at 80 °C for 15 h, followed by 70% cold work and subsequent final aging at 165 °C for 4 h, which resulted in the FYS of about 480 MPa. As for the elongation, the optimum condition was pre-aging at 80 °C for 15 h, followed by 30% cold work and final-aging at 165 °C for 4 h, which led to 21% elongation. To verify the suggested optimum conditions, the tests were carried out confirming the high accuracy (above 94%) of the RSM technique as well as the developed models. It is shown that the RSM can be used successfully to optimize the aging process, to determine the significance of aging parameters and to model the combination effect of process variables on the aging behavior of AA6056.