A multistep process of cancer associated fibroblasts determination under CSL-p53 control

Stromal fibroblast senescence has been linked to the aging-associated increase of tumors. However, in epithelial cancer, density and proliferation of cancer associated fibroblasts (CAF) are frequently increased, rather than decreased. We previously showed that genetic deletion or down-modulation of the canonical Notch effector CSL/RBP-JK in dermal fibroblasts is sufficient for CAF activation with consequent development of keratinocyte-derived tumors. We show here that CSL silencing induces senescence of primary fibroblasts from dermis, oral mucosa, breast and lung. CSL functions in these cells as direct repressor of multiple senescence- and CAF-effector genes. It also physically interacts with p53, repressing its activity. CSL is down-modulated in stromal fibroblasts of premalignant skin actinic keratosis lesions and squamous cell carcinomas (SCC), while p53 gene expression and function is down-modulated only in the latter, with paracrine influences of incipient cancer cells as a likely culprit. Concomitant loss of CSL and p53 overcomes fibroblast senescence, enhances CAF effector gene expression and promotes stromal and cancer cell expansion. The findings support a CAF activation/stromal co-evolution model under convergent CSL/p53 control of likely clinical relevance.

Repetitive Deliberate Fires: Critical Review of the Situation and Proposal of a Follow-Up Process and Systematic Analysis

Deliberate fires appear to be borderless and timeless events creating a serious security problem. There have been many attempts to develop approaches to tackle this problem, but unfortunately acting effectively against deliberate fires has proven a complex challenge. This article reviews the current situation relating to deliberate fires: what do we know, how serious is the situation, how is it being dealt with, and what challenges are faced when developing a systematic and global methodology to tackle the issues? The repetitive nature of some types of deliberate fires will also be discussed. Finally, drawing on the reality of repetition within deliberate fires and encouraged by successes obtained in previous repetitive crimes (such as property crimes or drug trafficking), we will argue that the use of the intelligence process cycle as a framework to allow a follow-up and systematic analysis of fire events is a relevant approach. This is the first article of a series of three articles. This first part is introducing the context and discussing the background issues in order to provide a better underpinning knowledge to managers and policy makers planning on tackling this issue. The second part will present a methodology developed to detect and identify repetitive fire events from a set of data, and the third part will discuss the analyses of these data to produce intelligence.

What can ecosystems learn? Expanding evolutionary ecology with learning theory.

BACKGROUND: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? RESULTS: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. CONCLUSIONS: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions. REVIEWERS: This article was reviewed by Prof. Ricard V Solé, Universitat Pompeu Fabra, Barcelona and Prof. Rob Knight, University of Colorado, Boulder.

The forced adoption of a fast-track appraisal process for a breast cancer treatment in UK

Trastuzumab (Herceptin ®, Roche) is approved in UK for the treatment of the metastatic breast cancer since 2001. As of 2005, concomitantly with the publication of 3 studies that showed it produces a 50% reduction of the recurrence rates of breast cancer, trastuzumab started to be prescribed in the earlt adjuvant treatrnent of this disease. Und June 2006, trastuzumab did not have both: 1) regulatory approval and 2) NICE [National Institute for Health and Clinical Excellence] recommendation for the use in early stages of breast cancer. During the period until June 2006, the trastuzumab use in those patients was not reimbursed and because the cost of trastuzumab is equal with the yearly UK average income, most of patients could not self fund their treatrnent. Before the publication of the final NICE guidance, the new data of trastuzumab in early breast cancer raised enormous patient and professional interest and expectations. A great volume of public and professional pressure was generated to transcend a system by which Primary Care Trusts can reimburse a treatment only after a formal guidance was issued. This paper draw on a case study depicting and analyzing the process by which regulatory approval and NICE recommendations were achieved in a record time and how trastuzumab became a standard treatment on early adjuvant breast cancer. According to the data we gathered in this work we were witnessing one of the fastest processes of adoption of a health care technology since the creation of NICE, in 1999. This study addresses the following research question: How and why does the adoption pattern of trastuzumab differ from the rational decision-making model of the reimbursement process in UK? [Author, p. 4]

To analyse a trace or not? Evaluating the decision-making process in the criminal investigation

In order to broaden our knowledge and understanding of the decision steps in the criminal investigation process, we started by evaluating the decision to analyse a trace and the factors involved in this decision step. This decision step is embedded in the complete criminal investigation process, involving multiple decision and triaging steps. Considering robbery cases occurring in a geographic region during a 2-year-period, we have studied the factors influencing the decision to submit biological traces, directly sampled on the scene of the robbery or on collected objects, for analysis. The factors were categorised into five knowledge dimensions: strategic, immediate, physical, criminal and utility and decision tree analysis was carried out. Factors in each category played a role in the decision to analyse a biological trace. Interestingly, factors involving information available prior to the analysis are of importance, such as the fact that a positive result (a profile suitable for comparison) is already available in the case, or that a suspect has been identified through traditional police work before analysis. One factor that was taken into account, but was not significant, is the matrix of the trace. Hence, the decision to analyse a trace is not influenced by this variable. The decision to analyse a trace first is very complex and many of the tested variables were taken into account. The decisions are often made on a case-by-case basis.