Treatment rationale study design for the MetLung trial : a randomized, double-blind phase III study of onartuzumab (MetMAb) in combination with erlotinib versus erlotinib alone in patients who have received standard chemotherapy for stage IIIB or IV met-positive non-small-cell lung cancer

We present the treatment rationale and study design of the MetLung phase III study. This study will investigate onartuzumab (MetMAb) in combination with erlotinib compared with erlotinib alone, as second- or third-line treatment, in patients with advanced non-small-cell lung cancer (NSCLC) who are Met-positive by immunohistochemistry. Approximately 490 patients (245 per treatment arm) will receive erlotinib (150 mg oral daily) plus onartuzumab or placebo (15 mg/kg intravenous every 3 weeks) until disease progression, unacceptable toxicity, patient or physician decision to discontinue, or death. The efficacy objectives of this study are to compare overall survival (OS) (primary endpoint), progression-free survival, and response rates between the 2 treatment arms. In addition, safety, quality of life, pharmacokinetics, and translational research will be investigated across treatment arms. If the primary objective (OS) is achieved, this study will provide robust results toward an alternative treatment option for patients with Met-positive second- or third-line NSCLC. © 2012 Elsevier Inc. All Rights Reserved.

Phase II trial of Oxaliplatin and 5-Fluorouracil/Leucovorin combination in epithelial ovarian carcinoma relapsing within 2 years of platinum-based therapy

Objective To evaluate the efficacy and toxicity of Oxaliplatin and 5-Fluorouracil (5-FU)/Leucovorin (LV) combination in ovarian cancer relapsing within 2 years of prior platinum-based chemotherapy in a phase II trial. Methods Eligible patients had at least one prior platinum-based chemotherapy regimen, elevated CA-125 ≥ 60 IU/l, radiological evidence of disease progression and adequate hepatic, renal and bone marrow function. Patients with raised CA-125 levels alone as marker of disease relapse were not eligible. Oxaliplatin (85 mg/m 2) was given on day 1, and 5-Fluorouracil (370 mg/m 2) and Leucovorin (30 mg) was given on days 1 and 8 of a 14-day cycle. Results Twenty-seven patients were enrolled. The median age was 57 years (range 42-74 years). The median platinum-free interval (PFI) was 5 months (range 0-17 months) with only 30% of patients being platinum sensitive (PFI > 6 months). Six patients (22%) had two prior regimens of chemotherapy. A total of 191 cycles were administered (median 7; range 2-12). All patients were evaluable for toxicity. The following grade 3/4 toxicities were noted: anemia 4%; neutropenia 15%; thrombocytopenia 11%; neurotoxicity 8%; lethargy 4%; diarrhea 4%; hypokalemia 11%; hypomagnesemia 11%. Among 27 enrolled patients, 20 patients were evaluable for response by WHO criteria and 25 patients were evaluable by Rustin's CA-125 criteria. The overall response rate (RR) by WHO criteria was 30% (95% CI: 15- 52) [three complete responses (CRs) and three partial responses (PRs)]. The CA-125 response rate was 56% (95% CI: 37-73). Significantly, a 25% (95% CI: 9-53) radiological and a 50% (95% CI: 28-72) CA-125 response rate were noted in platinum resistant patients (PFI < 6 months). The median response duration was 4 months (range 3-12) and the median overall survival was 10 months. Conclusion Oxaliplatin and 5-Fluorouracil/ Leucovorin combination has a good safety profile and is active in platinum-pretreated advanced epithelial ovarian cancer. © 2004 Elsevier Inc. All rights reserved.

The combination of empirical mode decomposition and minimum entropy deconvolution for roller bearing diagnostics in non-stationary operation

Diagnostics is based on the characterization of mechanical system condition and allows early detection of a possible fault. Signal processing is an approach widely used in diagnostics, since it allows directly characterizing the state of the system. Several types of advanced signal processing techniques have been proposed in the last decades and added to more conventional ones. Seldom, these techniques are able to consider non-stationary operations. Diagnostics of roller bearings is not an exception of this framework. In this paper, a new vibration signal processing tool, able to perform roller bearing diagnostics in whatever working condition and noise level, is developed on the basis of two data-adaptive techniques as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED), coupled by means of the mathematics related to the Hilbert transform. The effectiveness of the new signal processing tool is proven by means of experimental data measured in a test-rig that employs high power industrial size components.

Results using Trabecular Metal™ augments in combination with acetabular impaction bone grafting in deficient acetabula

We examined whether the use of trabecular metal wedges to fill segmental defects is an effective method of socket reconstruction when used in combination with impaction grafting and implantation of a cemented socket. Fifteen hips in 14 patients underwent impaction grafting in combination with a TM wedge with a minimum of 2 years follow-up. All patients had their defects assessed using the Paprosky classification. Patients were reviewed with x-rays and migration of the implant was measured. Outcome scores were also collected. Mean follow-up was 39 months (25-83). The mean age at surgery was 67.8 (49-85) years. Seven of the patients had previously undergone impaction grafting with the use of a stainless steel rim mesh to constrain the graft. None of the patients had failed either clinically or radiologically.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

A rule-based hybrid method for anomaly detection in online-social-network graphs

Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

A novel process of group-oriented question reduction for rule-based recommendation websites

Several websites utilise a rule-base recommendation system, which generates choices based on a series of questionnaires, for recommending products to users. This approach has a high risk of customer attrition and the bottleneck is the questionnaire set. If the questioning process is too long, complex or tedious; users are most likely to quit the questionnaire before a product is recommended to them. If the questioning process is short; the user intensions cannot be gathered. The commonly used feature selection methods do not provide a satisfactory solution. We propose a novel process combining clustering, decisions tree and association rule mining for a group-oriented question reduction process. The question set is reduced according to common properties that are shared by a specific group of users. When applied on a real-world website, the proposed combined method outperforms the methods where the reduction of question is done only by using association rule mining or only by observing distribution within the group.

Social tagging, guppy effect and the role of interference : a quantum-inspired model for tags combination

Social tagging systems are shown to evidence a well known cognitive heuristic, the guppy effect, which arises from the combination of different concepts. We present some empirical evidence of this effect, drawn from a popular social tagging Web service. The guppy effect is then described using a quantum inspired formalism that has been already successfully applied to model conjunction fallacy and probability judgement errors. Key to the formalism is the concept of interference, which is able to capture and quantify the strength of the guppy effect.

Beyond rule based reasoning - the meaning and use of cases

Commercial legal expert systems are invariably rule based. Such systems are poor at dealing with open texture and the argumentation inherent in law. To overcome these problems we suggest supplementing rule based legal expert systems with case based reasoning or neural networks. Both case based reasoners and neural networks use cases-but in very different ways. We discuss these differences at length. In particular we examine the role of explanation in existing expert systems methodologies. Because neural networks provide poor explanation facilities, we consider the use of Toulmin argument structures to support explanation (S. Toulmin, 1958). We illustrate our ideas with regard to a number of systems built by the authors

Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows

This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.

Controlled systemic release of interleukin-12 after gene electrotransfer to muscle for cancer gene therapy alone or in combination with ionizing radiation in murine sarcomas

Background: The present study aimed to evaluate the antitumor effectiveness of systemic interleukin (IL)-12 gene therapy in murine sarcoma models, and to evaluate its interaction with the irradiation of tumors and metastases. To avoid toxic side-effects of IL-12 gene therapy, the objective was to achieve the controlled release of IL-12 after intramuscular gene electrotransfer. Methods: Gene electrotransfer of the plasmid pORF-mIL12 was performed into the tibialis cranialis in A/J and C57BL/6 mice. Systemic release of the IL-12 was monitored in the serum of mice after carrying out two sets of intramuscular IL-12 gene electrotransfer of two different doses of plasmid DNA. The antitumor effectiveness of IL-12 gene electrotransfer alone or in combination with local tumor or lung irradiation with X-rays, was evaluated on subcutaneous SA-1 and LPB tumors, as well as on lung metastases. Results: A synergistic antitumor effect of intramuscular gene electrotransfer combined with local tumor irradiation was observed as a result of the systemic distribution of IL-12. The gene electrotransfer resulted in up to 28% of complete responses of tumors. In combination with local tumor irradiation, the curability was increased by up to 100%. The same effect was observed for lung metastases, where a potentiating factor of 1.3-fold was determined. The amount of circulating IL-12 was controlled by the number of repeats of gene electrotransfer and by the amount of the injected plasmid. Conclusions: The present study demonstrates the feasibility of treatment by IL-12 gene electrotransfer combined with local tumor or lung metastases irradiation on sarcoma tumors for translation into the clinical setting. Copyright © 2009 John Wiley & Sons, Ltd.

Targeted disruption of the JAK2/STAT3 pathway in combination with systemic administration of paclitaxel inhibits the priming of ovarian cancer stem cells leading to a reduced tumor burden

Chemotherapy resistance associated with recurrent disease is the major cause of poor survival of ovarian cancer patients. We have recently demonstrated activation of the JAK2/STAT3 pathway and the enhancement of a cancer stem cell (CSC)-like phenotype in ovarian cancer cells treated in vitro with chemotherapeutic agents. To elucidate further these mechanisms in vivo,we used a two-tiered paclitaxel treatment approach in nude mice inoculated with ovarian cancer cells. In the first approach, we demonstrate that a single intraperitoneal administration of paclitaxel in mice 7 days after subcutaneous transplantation of the HEY ovarian cancer cell line resulted in a significant increase in the expression of CA125, Oct4, and CD117 in mice xenografts compared to control mice xenografts which did not receive paclitaxel. In the second approach, mice were administered once weekly with paclitaxel and/or a daily dose of the JAK2-specific inhibitor, CYT387, over 4weeks. Mice receiving paclitaxel only demonstrated a significant decrease in tumor volume compared to control mice. At the molecular level, mouse tumors remaining after paclitaxel administration showed a significant increase in the expression of Oct4 and CD117 coinciding with a significant activation of the JAK2/STAT3 pathway compared to control tumors. The addition of CYT387 with paclitaxel resulted in the suppression of JAK2/STAT3 activation and abrogation of Oct4 and CD117 expression in mouse xenografts. This coincided with significantly smaller tumors in mice administered CYT387 in addition to paclitaxel, compared to the control group and the group of mice receiving paclitaxel only. These data suggest that the systemic administration of paclitaxel enhances Oct4- and CD117-associated CSC-like marker expression in surviving cancer cells in vivo, which can be suppressed by the addition of the JAK2-specific inhibitor CYT387, leading to a significantly smaller tumor burden. These novel findings have the potential for the development of CSC-targeted therapy to improve the treatment outcomes of ovarian cancer patients.

Network-targeted combination therapy : a new concept in cancer treatment

Toxicity is a major concern for anti-neoplastic drugs, with much of the existing pharmacopoeia being characterized by a very narrow therapeutic index. 'Network-targeted' combination therapy is a promising new concept in cancer therapy, whereby therapeutic index might be improved by targeting multiple nodes in a cell's signaling network, rather than a single node. Here, we examine the potential of this novel approach, illustrating how therapeutic benefit could be achieved with smaller doses of the necessary agents.

The rule of law, the public interest and the management of natural resources in Australia

The statutory arrangements for the management of natural resources in Australia confer powers of decision-making upon government agencies and, at the same time, restrict how these powers are to be exercised by reference either to stated criteria or in some instances to the public interest. These restrictions perform different functions according to their structure, form and language: for example they may be in the form of jurisdictional, deliberative or purposive rules. This article reviews how the offshore resources legislation of the Commonwealth and some examples of the onshore resources legislation of Queensland address the functions performed by the public interest in determining whether there is compliance with the principle of the rule of law.

On the effect of topology on cellular automata rule spaces

This thesis presents an empirical study of the effects of topology on cellular automata rule spaces. The classical definition of a cellular automaton is restricted to that of a regular lattice, often with periodic boundary conditions. This definition is extended to allow for arbitrary topologies. The dynamics of cellular automata within the triangular tessellation were analysed when transformed to 2-manifolds of topological genus 0, genus 1 and genus 2. Cellular automata dynamics were analysed from a statistical mechanics perspective. The sample sizes required to obtain accurate entropy calculations were determined by an entropy error analysis which observed the error in the computed entropy against increasing sample sizes. Each cellular automata rule space was sampled repeatedly and the selected cellular automata were simulated over many thousands of trials for each topology. This resulted in an entropy distribution for each rule space. The computed entropy distributions are indicative of the cellular automata dynamical class distribution. Through the comparison of these dynamical class distributions using the E-statistic, it was identified that such topological changes cause these distributions to alter. This is a significant result which implies that both global structure and local dynamics play a important role in defining long term behaviour of cellular automata.