Towards a novel biologically-inspired cloud elasticity framework

With the widespread use of the Internet, the popularity of web applications has significantly increased. Such applications are subject to unpredictable workload conditions that vary from time to time. For example, an e-commerce website may face higher workloads than normal during festivals or promotional schemes. Such applications are critical and performance related issues, or service disruption can result in financial losses. Cloud computing with its attractive feature of dynamic resource provisioning (elasticity) is a perfect match to host such applications. The rapid growth in the usage of cloud computing model, as well as the rise in complexity of the web applications poses new challenges regarding the effective monitoring and management of the underlying cloud computational resources. This thesis investigates the state-of-the-art elastic methods including the models and techniques for the dynamic management and provisioning of cloud resources from a service provider perspective. An elastic controller is responsible to determine the optimal number of cloud resources, required at a particular time to achieve the desired performance demands. Researchers and practitioners have proposed many elastic controllers using versatile techniques ranging from simple if-then-else based rules to sophisticated optimisation, control theory and machine learning based methods. However, despite an extensive range of existing elasticity research, the aim of implementing an efficient scaling technique that satisfies the actual demands is still a challenge to achieve. There exist many issues that have not received much attention from a holistic point of view. Some of these issues include: 1) the lack of adaptability and static scaling behaviour whilst considering completely fixed approaches; 2) the burden of additional computational overhead, the inability to cope with the sudden changes in the workload behaviour and the preference of adaptability over reliability at runtime whilst considering the fully dynamic approaches; and 3) the lack of considering uncertainty aspects while designing auto-scaling solutions. This thesis seeks solutions to address these issues altogether using an integrated approach. Moreover, this thesis aims at the provision of qualitative elasticity rules. This thesis proposes a novel biologically-inspired switched feedback control methodology to address the horizontal elasticity problem. The switched methodology utilises multiple controllers simultaneously, whereas the selection of a suitable controller is realised using an intelligent switching mechanism. Each controller itself depicts a different elasticity policy that can be designed using the principles of fixed gain feedback controller approach. The switching mechanism is implemented using a fuzzy system that determines a suitable controller/- policy at runtime based on the current behaviour of the system. Furthermore, to improve the possibility of bumpless transitions and to avoid the oscillatory behaviour, which is a problem commonly associated with switching based control methodologies, this thesis proposes an alternative soft switching approach. This soft switching approach incorporates a biologically-inspired Basal Ganglia based computational model of action selection. In addition, this thesis formulates the problem of designing the membership functions of the switching mechanism as a multi-objective optimisation problem. The key purpose behind this formulation is to obtain the near optimal (or to fine tune) parameter settings for the membership functions of the fuzzy control system in the absence of domain experts’ knowledge. This problem is addressed by using two different techniques including the commonly used Genetic Algorithm and an alternative less known economic approach called the Taguchi method. Lastly, we identify seven different kinds of real workload patterns, each of which reflects a different set of applications. Six real and one synthetic HTTP traces, one for each pattern, are further identified and utilised to evaluate the performance of the proposed methods against the state-of-the-art approaches

Human epididymis protein 4 reference limits and natural variation in a Nordic reference population

The objectives of this study are to establish reference limits for human epididymis protein 4, HE4, and investigate factors influencing HE4 levels in healthy subjects. HE4 was measured in 1,591 samples from the Nordic Reference Interval Project Bio-bank and Database biobank, using the manual HE4 EIA (Fujirebio) for 802 samples and the Architect HE4 (Abbott) for 792 samples. Reference limits were calculated using the statistical software R. The influence of donor characteristics such as age, sex, body mass index, smoking habits, and creatinine on HE4 levels was investigated using a multivariate model. The study showed that age is the main determinant of HE4 in healthy subjects, corresponding to 2% higher HE4 levels at 30 years (compared to 20 years), 9% at 40 years, 20% at 50 years, 37% at 60 years, 63% at 70 years, and 101% at 80 years. HE4 levels are 29% higher in smokers than in nonsmokers. In conclusion, HE4 levels in healthy subjects are associated with age and smoking status. Age-dependent reference limits are suggested

The impact of comorbidity and stage on ovarian cancer mortality: A nationwide Danish cohort study

<p>Abstract</p> <p>Background</p> <p>The incidence of ovarian cancer increases sharply with age, and many elderly patients have coexisting diseases. If patients with comorbidities are diagnosed with advanced stages, this would explain the poor survival observed among ovarian cancer patients with severe comorbidity. Our aims were to examine the prevalence of comorbidity according to stage of cancer at diagnosis, to estimate the impact of comorbidity on survival, and to examine whether the impact of comorbidity on survival varies by stage.</p> <p>Methods</p> <p>From the Danish Cancer Registry we identified 5,213 patients (> 15 years old) with ovarian cancer diagnosed from 1995 to 2003. We obtained information on comorbidities from the Danish National Hospital Discharge Registry. Vital status was determined through linkage to the Civil Registration System. We estimated the prevalence of comorbidity by stage and computed absolute survival and relative mortality rate ratios (MRRs) by comorbidity level (Charlson Index score 0, 1–2, 3+), using patients with Charlson Index score 0 as the reference group. We then stratified by stage and computed the absolute survival and MRRs according to comorbidity level, using patients with Charlson score 0 and localized tumour/FIGO I as the reference group. We adjusted for age and calendar time.</p> <p>Results</p> <p>Comorbidity was more common among patients with an advanced stage of cancer. One- and five-year survival was higher in patients without comorbidity than in patients with registered comorbidity. After adjustment for age and calendar time, one-year MRRs declined from 1.8 to 1.4 and from 2.7 to 2.0, for patients with Charlson scores 1–2 and 3+, respectively. After adjustment for stage, the MRRs further declined to 1.3 and 1.8, respectively. Five-year MRRs declined similarly after adjustment for age, calendar time, and stage. The impact of severe comorbidity on mortality varied by stage, particularly among patients with tumours with regional spread/FIGO-stages II and III.</p> <p>Conclusion</p> <p>The presence of severe comorbidity was associated with an advanced stage of ovarian cancer. Mortality was higher among patients with comorbidities and the impact of comorbidity varied by stage.</p

MicroRNA Expression and Regulation in Human Ovarian Carcinoma Cells by Luteinizing Hormone

MicroRNAs have been widely-studied with regard to their aberrant expression and high correlation with tumorigenesis and progression in various solid tumors. With the major goal of assessing gonadotropin (luteinizing hormone, LH) contributions to LH receptor (LHR)-positive ovarian cancer cells, we have conducted a genome-wide transcriptomic analysis on human epithelial ovarian cancer cells to identify the microRNA-associated cellular response to LH-mediated activation of LHR.Human ovarian cancer cells (SKOV3) were chosen as negative control (LHR-) and stably transfected to express functional LHR (LHR+), followed by incubation with LH (0-20 h). At different times of LH-mediated activation of LHR the cancer cells were analyzed by a high-density Ovarian Cancer Disease-Specific-Array (DSA, ALMAC™), which profiled ∼ 100,000 transcripts with ∼ 400 non-coding microRNAs.In total, 65 microRNAs were identified to exhibit differential expression in either LHR expressing SKOV3 cells or LH-treated cells, a few of which have been found in the genomic fragile regions that are associated with abnormal deletion or amplification in cancer, such as miR-21, miR-101-1, miR-210 and miR-301a. By incorporating the dramatic expression changes observed in mRNAs, strong microRNA/mRNA regulatory pairs were predicted through statistical analyses coupled with collective computational prediction. The role of each microRNA was then determined through a functional analysis based on the highly-confident microRNA/mRNA pairs.The overall impact on the transcriptome-level expression indicates that LH may regulate apoptosis and cell growth of LHR+ SKOV3 cells, particularly by reducing cancer cell proliferation, with some microRNAs involved in regulatory roles

C-Fos expression is a molecular predictor of progression and survival in epithelial ovarian carcinoma

Members of the Fos protein family dimerise with Jun proteins to form the AP-1 transcription factor complex. They have a central function in proliferation and differentiation of normal tissue as well as in oncogenic transformation and tumour progression. We analysed the expression of c-Fos, FosB, Fra-1 and Fra-2 to investigate the function of Fos transcription factors in ovarian cancer. A total of 101 patients were included in the study. Expression of Fos proteins was determined by western blot analysis, quantified by densitometry and verified by immunohistochemistry. Reduced c-Fos expression was independently associated with unfavourable progression-free survival (20.6, 31.6 and 51.2 months for patients with low, moderate and high c-Fos expression; P=0.003) as well as overall survival (23.8, 46.0 and 55.5 months for low, moderate and high c-Fos levels; P=0.003). No correlations were observed for FosB, Fra-1 and Fra-2. We conclude that loss of c-Fos expression is associated with tumour progression in ovarian carcinoma and that c-Fos may be a prognostic factor. These results are in contrast to the classic concept of c-Fos as an oncogene, but are supported by the recently discovered tumour-suppressing and proapoptotic function of c-Fos in various cancer types

Variability in chemotherapy delivery for elderly women with advanced stage ovarian cancer and its impact on survival

Given the survival benefits of adjuvant chemotherapy for advanced ovarian cancer (OC), we examined the associations of survival with the time interval from debulking surgery to initiation of chemotherapy and with the duration of chemotherapy. Among patients ⩾65 years with stages III/IV OC diagnosed between 1991 and 2002 in the Surveillance, Epidemiology, and End Results-Medicare database, we developed regression models of predictors of the time interval from surgery to initiation of chemotherapy and of the total duration of chemotherapy. Survival was examined with Cox proportional hazards models. Among 2558 patients, 1712 (67%) initiated chemotherapy within 6 weeks of debulking surgery, while 846 (33%) began treatment >6 weeks. Older age, black race, being unmarried, and increased comorbidities were associated with delayed initiation of chemotherapy. Delay of chemotherapy was associated with an increase in mortality (hazard ratio (HR)=1.11; 95% CI, 1.0–1.2). Among 1932 patients in the duration of treatment analysis, the 1218 (63%) treated for 3–7 months had better survival than the 714 (37%) treated for ⩽3 months (HR=0.84; 95% CI, 0.75–0.94). This analysis represents one of the few studies describing treatment delivery and outcome in women with advanced OC. Delayed initiation and early discontinuation of chemotherapy were common and associated with increased mortality

Combinatorial Effect of Non-Steroidal Anti-inflammatory Drugs and NF-κB Inhibitors in Ovarian Cancer Therapy

Several epidemiological studies have correlated the use of non-steroidal anti-inflammatory drugs (NSAID) with reduced risk of ovarian cancer, the most lethal gynecological cancer, diagnosed usually in late stages of the disease. We have previously established that the pro-apoptotic cytokine melanoma differentiation associated gene-7/Interleukin-24 (mda-7/IL-24) is a crucial mediator of NSAID-induced apoptosis in prostate, breast, renal and stomach cancer cells. In this report we evaluated various structurally different NSAIDs for their efficacies to induce apoptosis and mda-7/IL-24 expression in ovarian cancer cells. While several NSAIDs induced apoptosis, Sulindac Sulfide and Diclofenac most potently induced apoptosis and reduced tumor growth. A combination of these agents results in a synergistic effect. Furthermore, mda-7/IL-24 induction by NSAIDs is essential for programmed cell death, since inhibition of mda-7/IL-24 by small interfering RNA abrogates apoptosis. mda-7/IL-24 activation leads to upregulation of growth arrest and DNA damage inducible (GADD) 45 α and γ and JNK activation. The NF-κB family of transcription factors has been implicated in ovarian cancer development. We previously established NF-κB/IκB signaling as an essential step for cell survival in cancer cells and hypothesized that targeting NF-κB could potentiate NSAID-mediated apoptosis induction in ovarian cancer cells. Indeed, combining NSAID treatment with NF-κB inhibitors led to enhanced apoptosis induction. Our results indicate that inhibition of NF-κB in combination with activation of mda-7/IL-24 expression may lead to a new combinatorial therapy for ovarian cancer