Multi-behavior agent model for supply chain management

Recent economic and international threats to occidental industries have encouraged companies to rethink their planning systems. Due to consolidation, the development of integrated supply chains and the use of inter-organizational information systems have increased business interdependencies and the need for collaboration. Thus, agility and the ability to deal quickly with disturbances in supply chains are critical to maintain overall performance. In order to develop tools to increase the agility of the supply chain and to promote the collaborative management of such disturbances, agent-based technology takes advantage of the ability of agents to make autonomous decisions in a distributed network. This paper proposes a multi-behavior agent model using different decision making approaches in a context where planning decisions are supported by a distributed advanced planning system (d-APS). The implementation of this solution is realized through the FOR@C experimental agent-based platform, dedicated to the supply chain planning for the forest products industry

Multi-Behavior Agent Model for Supply Chain Management

Recent economic and international threats to occidental industries have encouraged companies to rethink their planning systems. Due to consolidation, the development of integrated supply chains and the use of inter-organizational information systems have increased business interdependencies and the need for collaboration. Thus, agility and the ability to deal quickly with disturbances in supply chains are critical to maintain overall performance. In order to develop tools to increase the agility of the supply chain and to promote the collaborative management of such disturbances, agent-based technology takes advantage of the ability of agents to make autonomous decisions in a distributed network. This paper proposes a multi-behavior agent model using different decision making approaches in a context where planning decisions are supported by a distributed advanced planning system (d-APS). The implementation of this solution is realized through the FOR@C experimental agent-based platform, dedicated to the supply chain planning for the forest products industry

Cancer surgery induces inflammation, immunosuppression and neo-angiogenesis, but is it influenced by analgesics?

Grant information: This work was exclusively supported by the Department of Anesthesiology of the Université catholique de Louvain, St-Luc Hospital, Belgium. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptPeer reviewedPublisher PD

Pain management in living related adult donor hepatectomy : feasibility of an evidence-based protocol in 100 consecutive donors

Peer reviewedPublisher PD

Impact of durum wheat milling on the deoxynivalenol distribution in the outcoming fractions

International audienceThe milling behavior of two naturally infected samples from durum wheat grains displaying contrasting levels of mycotoxins were analyzed. Although the two samples showed a similar milling behavior, an increase of about twenty percent in deoxynivalenol level was found in semolina from the sample containing the higher amount of mycotoxins. However, even if the highest concentration of deoxynivalenol was found in fractions originating from the grain outer layers, the mycotoxin contamination in semolina and flours were not related to the amount of two biochemical compounds (ash or phytic acid) that could be used as markers to monitor these external tissues. Presence of the trichothecene-producing fungi in the most internal semolina fraction was also shown using specific DNA primers and PCR amplification. Comparison between deoxynivalenol concentration in the feedings and corresponding output at each milling step or grinding of semolina fractions followed by sizing showed that mycotoxin concentration occurs in the finest particles at the first processing steps. Therefore, deoxynivalenol contamination of the milling fractions is not simply due to the presence of peripheral grain tissues

Reduction of Breast Cancer Relapses with Perioperative Non-Steroidal Anti-Inflammatory Drugs: New Findings and a Review

To explain a bimodal pattern of hazard of relapse among early stage breast cancer patients identified in multiple databases, we proposed that late relapses result from steady stochastic progressions from single dormant malignant cells to avascular micrometastases and then on to growing deposits. However in order to explain early relapses, we had to postulate that something happens at about the time of surgery to provoke sudden exits from dormant phases to active growth and then to detection. Most relapses in breast cancer are in the early category. Recent data from Forget et al. suggest an unexpected mechanism. They retrospectively studied results from 327 consecutive breast cancer patients comparing various perioperative analgesics and anesthetics in one Belgian hospital and one surgeon. Patients were treated with mastectomy and conventional adjuvant therapy. Relapse hazard updated Sept 2011 are presented. A common Non-Steroidal Anti-Inflammatory Drug (NSAID) analgesic used in surgery produced far superior disease-free survival in the first 5 years after surgery. The expected prominent early relapse events in months 9-18 are reduced 5-fold. If this observation holds up to further scrutiny, it could mean that the simple use of this safe, inexpensive and effective anti-inflammatory agent at surgery might eliminate early relapses. Transient systemic inflammation accompanying surgery could facilitate angiogenesis of dormant micrometastases, proliferation of dormant single cells, and seeding of circulating cancer stem cells (perhaps in part released from bone marrow) resulting in early relapse and could have been effectively blocked by the perioperative anti-inflammatory agent

Promising development from translational or perhaps anti-translational research in breast cancer

Background: A great deal of the public’s money has been spent on cancer research but demonstrable benefits to patients have not been proportionate. We are a group of scientists and physicians who several decades ago were confronted with bimodal relapse patterns among early stage breast cancer patients who were treated by mastectomy. Since the bimodal pattern was not explainable with the then well-accepted continuous growth model, we proposed that metastatic disease was mostly inactive before surgery but was driven into growth somehow by surgery. Most relapses in breast cancer would fall into the surgery-induced growth category thus it was highly important to understand the ramifications of this process and how it may be curtailed. With this hypothesis, we have been able to explain a wide variety of clinical observations including why mammography is less effective for women age 40–49 than it is for women age 50–59, why adjuvant chemotherapy is most effective for premenopausal women with positive lymph nodes, and why there is a racial disparity in outcome. Methods: We have been diligently looking for new clinical or laboratory information that could provide a connection or correlation between the bimodal relapse pattern and some clinical factor or interventional action and perhaps lead us towards methods to prevent surgery-initiated tumor activity. Results: A recent development occurred when a retrospective study appeared in an anesthesiology journal that suggested the perioperative NSAID analgesic ketorolac seems to reduce early relapses following mastectomy. Collaborating with these anesthesiologists to understand this effect, we independently re-examined and updated their data and, in search of a mechanism, focused in on the transient systemic inflammation that follows surgery to remove a primary tumor. We have arrived at several possible explanations ranging from mechanical to biological that suggest the relapses avoided in the early years do not show up later. Conclusions: We present the possibility that a nontoxic and low cost intervention could prevent early relapses. It may be that preventing systemic inflammation post surgery will prevent early relapses. This could be controlled by the surgical anesthesiologist’s choice of analgesic drugs. This development needs to be confirmed in a randomized controlled clinical trial and we have identified triple negative breast cancer as the ideal subset with which to test this. If successful, this would be relatively easy to implement in developing as well as developed countries and would be an important translational result