Biological properties of adriamycin bound to biodegradable polymeric carriers

Three different conjugates having adriamycin (ADR) bound to the side chain carboxyl groups of high-molecular weight poly (¿--glutamic acid) (PGA) either directly or by interpolation of GlyGly and GlyGlyGlyLeu spacers, respectively, were compared with respect to immunogenicity and cytotoxicity in mice as well as release of drug by lysosomal enzymes. The cytotoxic efficacy of a single i.p. dose of each conjugate (5 mg ADR-equiv./kg) against L1210 leukemia cells implanted i.p. in DBA2 mice was studied by monitoring the survival time, the body weight and the number of long-term survivors (LTS). PGA-GlyGlyGlyLeu-ADR and PGA-GlyGly-ADR significantly enhanced the mean survival time (MST) of treated animals compared with the untreated control group (T/C 148¿149%) as did free ADR (T/C 147%). The tetrapeptide-spacer containing conjugate effected the presence of LTS at day 50 (2/5) as did free ADR (1/5).\ud \ud The secondary antibody response of the drug conjugates elicited in A/J mice after repeated dosage (125 ¿g/mouse) at day 0, 14 and 28 was evaluated at day 35 using the ELISA technique. IgG titers varied from a very low value (PGA-GlyGlyGlyLeu-ADR) to moderately high levels (PGA-ADR, PGA-GlyGly-ADR) which are 2¿3 orders of magnitude below that obtained for the strong immunogen bovine IgG. The data suggest that certain parts on the surface of the conjugates are immunogenic.\ud \ud The release of extractable low-molecular weight products from the conjugates mediated by lysosomal enzymes was analyzed using reversed-phase HPLC. The release profile of ADR as well as Gly-ADR, Leu-ADR or GlyLeu-ADR was determined. The total amount of ADR released after 77 h was 3.6% for PGA-GlyGlyGly-Leu-ADR, 1.0% for PGA-GlyGly-ADR and 0.5% for PGA-ADR. With all conjugates unidentified products were produced.\ud \ud It is proposed that the mechanism of action of the polymeric conjugates under in vivo conditions may be due to pinocytic capture followed by lysosomal degradation with release of ADR

Configuring heterogeneous wireless sensor networks under quality-of-service constraints

Wireless sensor networks (WSNs) are useful for a diversity of applications, such as structural monitoring of buildings, farming, assistance in rescue operations, in-home entertainment systems or to monitor people's health. A WSN is a large collection of small sensor devices that provide a detailed view on all sides of the area or object one is interested in. A large variety of WSN hardware platforms is readily available these days. Many operating systems and protocols exist to support essential functionality such as communication, power management, data fusion, localisation, and much more. A typical sensor node has a number of settings that affect its behaviour and the function of the network itself, such as the transmission power of its radio and the number of measurements taken by its sensor per minute. As the number of nodes in a WSN may be very large, the collection of independent parameters in these networks – the configuration space – tends to be enormous. The user of the WSN would have certain expectations on the Quality of Service (QoS) of the network. A WSN is deployed for a specific purpose, and has a number of measurable properties that indicate how well the network's task is being performed. Examples of such quality metrics are the time needed for measured information to reach the user, the degree of coverage of the area, or the lifetime of the network. Each point in the configuration space of the network gives rise to a certain value in each of the quality metrics. The user may place constraints on the quality metrics, and wishes to optimise the configuration to meet their goals. Work on sensor networks often focuses on optimising only one metric at the time, ignoring the fact that improving one aspect of the system may deteriorate other important performance characteristics. The study of trade-offs between multiple quality metrics, and a method to optimally configure a WSN for several objectives simultaneously – until now a rather unexplored field – is the main contribution of this thesis. There are many steps involved in the realisation of a WSN that is fulfilling a task as desired. First of all, the task needs to be defined and specified, and appropriate hardware (sensor nodes) needs to be selected. After that, the network needs to be deployed and properly configured. This thesis deals with the configuration problem, starting with a possibly heterogeneous collection of nodes distributed in an area of interest, suitable models of the nodes and their interaction, and a set of task-level requirements in terms of quality metrics. We target the class of WSNs with a single data sink that use a routing tree for communication. We introduce two models of tasks running on a sensor network – target tracking and spatial mapping – which are used in the experiments in this thesis. The configuration process is split in a number of phases. After an initialisation phase to collect information about the network, the routing tree is formed in the second configuration phase. We explore the trade-off between two attributes of a tree: the average path length and the maximum node degree. These properties do not only affect the quality metrics, but also the complexity of the remaining optimisation trajectory. We introduce new algorithms to efficiently construct a shortest-path spanning tree in which all nodes have a degree not higher than a given target value. The next phase represents the core of the configuration method: it features a QoS optimiser that determines the Pareto-optimal configurations of the network given the routing tree. A configuration contains settings for the parameters of all nodes in the network, plus the metric values they give rise to. The Pareto-optimal configurations, also known as Pareto points, represent the best possible trade-offs between the quality metrics. Given the vastness of the configuration space, which is exponential in the size of the network, it is impossible to use a brute-force approach and try all possibilities. Still our method efficiently finds all Pareto points, by incrementally searching the configuration space, and discarding potential solutions immediately when they appear to be not Pareto optimal. An important condition for this to work is the ability to compute quality metrics for a group of nodes from the quality metrics of smaller groups of nodes. The precise requirements are derived and shown to hold for the example tasks. Experimental results show that the practical complexity of this algorithm is approximately linear in the number of nodes in the network, and thus scalable to very large networks. After computing the set of Pareto points, a configuration that satisfies the QoS constraints is selected, and the nodes are configured accordingly (the selection and loading phases). The configuration process can be executed in either a centralised or a distributed way. Centralised means that all computations are carried out on a central node, while the distributed algorithms do all the work on the sensor nodes themselves. Simulations show run times in the order of seconds for the centralised configuration of WSNs of hundreds of TelosB sensor nodes. The distributed algorithms take in the order of minutes for the same networks, but have a lower communication overhead. Hence, both approaches have their own pros and cons, and even a combination is possible in which the heavy work is performed by dedicated compute nodes spread across the network. Besides the trade-offs between quality metrics, there is a meta trade-off between the quality and the cost of the configuration process itself. A speed-up of the configuration process can be achieved in exchange for a reduction in the quality of the solutions. We provide complexity-control functionality to fine-tune this quality/cost trade-off. The methods described thus far configure a WSN given a fixed state (node locations, environmental conditions). WSNs, however, are notoriously dynamic during operation: nodes may move or run out of battery, channel conditions may fluctuate, or the demands from the user may change. The final part of this thesis describes methods to adapt the configuration to such dynamism at run time. Especially the case of a mobile sink is treated in detail. As frequently doing global reconfigurations would likely be too slow and too expensive, we use localised algorithms to maintain the routing tree and reconfigure the node parameters. Again, we are able to control the quality/cost trade-off, this time by adjusting the size of the locality in which the reconfiguration takes place. To conclude the thesis, a case study is presented, which highlights the use of the configuration method on a more complex example containing a lot of heterogeneity

TBD

As a long time, System Safety engineer, working on major programs that implement system safety programs in accordance with Mil-Std-882, I understand that the topic of this post is rather controversial since it questions one of the main tenets of the profession – that a formal risk assessment based upon a pre-established Risk Assessment Matrix is a necessary part of the process

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This TBD column finds me in a rather different place than I was just a couple of years ago. At that time, I made an agreement with one of my senior engineers that I would keep my safety consulting business going until he reached his retirement age goal and I reached my 65th birthday. At that point, my plans were to “retire” in some way or another. Not completely retire, but reduce my staff and begin working part time instead of full time — and choose more interesting projects. In preparation for this event, my wife and I made a few changes to our living arrangement. This mainly involved paying off the remainder of the mortgage on our house and installing a 7 kW solar array. Those investments resulted in our having almost no mortgage and close to zero energy costs. So far this year, our total electric bill is about $20 after 10 months — including our air conditioning, swimming pool and hot tub electricity use. Now, we can comfortably live on Social Security. We also managed to put aside a retirement nest egg that allows us some flexibility to do things besides just existing on Social Security. I no longer have to work for a living; I now only work for fun

TBD

System safety engineering is much more than just influencing the development of safe systems, products or processes. As has been shown over decades of experience in a wide variety of programs, an effective system safety program also positively improves system effectiveness and reduces programmatic risks, including the identification of cost-effective, schedule-effective and safety-effective mitigation strategies. The timely avoidance of even one significant mishap can easily “pay” for the costs of a high-quality system safety program

TBD

What a year 2020 is turning out to be! First, I wondered what would happen to the airline industry,with the problems Boeing was having with the 737 Max grounding that resulted in hundreds of acres of land covered with unsold new planes — not to mention all the existing grounded planes around the world. Then, the COVID-19 “problem” changed almost instantly from “another problem in China” to a global pandemic. As I write this column, 2020 has seen widespread global demonstrations around the Black Lives Matter movement and police policies. Undoubtedly, the second half of the year will bring new and unexpected problems and “adventures” throughout the world

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A topic that seems to keep popping up is how the International System Safety Society can assist with helping new (or maybe not so new) system safety engineers advance their careers by providing mentoring opportunities. The role and importance of mentors and mentoring is a topic that is near and dear to me. I don’t know other people’s challenges and experiences with learning to become competent in a new field, but for me, it typically doesn’t happen until I have had a chance to be mentored by an expert. I can take years of classes, attend conferences, attend workshops, sit through lectures and generally stuff my mind with all sorts of theoretical knowledge, but until I have a chance to work side by side with an experienced and compassionate mentor, it just doesn’t sink in

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I have been asked to provide a summary/status report on our involvement with the Arizona State University (ASU) initiative to introduce the topic of “design for safety” into engineering courses. I will attempt to do that here, but I wish to point out that this effort has the potential to change some of the fundamental aspects of our understanding of the goals and operation of the International System Safety Society (ISSS). It is my opinion that this is the correct time to re-think the vision of the ISSS to reflect an expanded global role. The ASU initiative is just one piece of a multi-part effort to reposition the ISSS as the “go to” organization in the field of system safety engineering and management. The effects of sequestration have made it clear that, for the ISSS, depending upon government projects is unreasonable, risky and does not meet the much broader needs of global industry — or mankind. I believe it is time for the Society to step up and admit that we are the leading organization in the field of system safety (by whatever name that field is referred to by various organizations)

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I want to tell you a story about an encounter I had at a hotel bar in Lancaster California. I appreciate that at first it doesn’t appear to have anything to do with System Safety. Trust me, I think you will agree that perhaps there is an important lesson for us and the Society

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I have noticed that industries “new” to the concepts of system safety seem to have trouble understanding the implications and meaning of the risk assessments that are performed as part of a system safety analysis. For us old hands in the profession, these concepts are second nature and, therefore, we tend not to discuss them. I think that maybe it is worth revisiting these basic concepts from time to time. Who knows, maybe we (I) have been off base for all these years, and we might all learn something new from a discussion. The basic definition of risk — a combination of the severity of a mishap and the probability that the mishap will occur — seems clear, especially when combined with the definition of a “mishap” as “an event or series of events resulting in unintentional death, injury, occupational illness, damage to or loss of equipment or property, or damage to the environment” (as defined in MIL-STD-882E). Apparently, risk also has something to do with unintended negative impacts, the severity of those impacts and the likelihood that these negative impacts will occur. This is pretty close to an everyday use of the term. It is not quite as obvious as it looks, however, when attempting to assign a risk to an identified bad outcome