The Systems Biology of COVID-19 and the SARS-CoV-2 virus. The class will build a foundation that includes the emergence of complexity, simple biological subsystems, their reductionist and equivalent toy and organ-chip models, and the measurements required to specify model architecture and parameters. Applications to biology, physiology, medicine, chemical and biological defense, pharmacology, drug discovery, and toxicology. UGrad: PHYS 240 01 and BME 290B; Grad: PHYS 326 and BME 395C.
0. The concept of homeostasis is often discussed yet rarely elucidated as in the article.
ReplyDelete1. The key point that I learned was presented when discussing Chauvet and his work that showed nesting systems could be spontaneous and would provide additional stability. The concept being that cells into tissues, tissues into organs, and organs into organism, provides a level of robustness capable of adapting to situations. The idea is not for a specific cell to always survive but for the organism as a whole.
2. Networks diagrams are over-rated. They only show what is thought to be known. A network diagram derived from the protein-protein database only highlights the proteins that interact yet fails to account for other molecules. For example, glutathione reductase is an important protein for how cells deal with ROS yet rarely if at all interacts with other proteins so if you are looking at a network of response to ROS then glutathione does not appear.
3. How do small signaling molecules fit into modeling?
4. I thought this was a good review article but not the end all be all of modeling and networks for control.
0. Organs need to communicate to functions properly
ReplyDelete1. "Noise" can be good. Multiple organ failure result from functional organs getting too "out of sync" to communicate.
2. I'm curious about how it could be possible to "fix the network" faster a network fixes itself?
3. Explain scale free/ random networks in a more tangible way
4. OoCs will be small enough to cheaply get very high resolution MRIs of them. Has this been investigated?
Frank "Edad" Block, Jr.
ReplyDeleteSysBio13 Asgn_7B_Class_07_Article_16_2013_09_12
0. Knew: Heart rate variability. My Polar training watch does all this!
1. Learned: Breakdown of systems interconnectivity as a possible mechanism of disease in man
2. Pressing: Can we restore the systems interconnectivity as a treatment? As an example, can we program a cardiac pacemaker to pace with short, medium, and long term variability and not just at a constant rate? (Some pacemakers do respond to temperature and motion but they should vary “independently.”)
3. Presentation: Heart rate variability and health.
4. Thoughts: Cf. Charles Perrow’s book, “Normal Accidents.” He looks at shipping, aviation, space travel, nuclear power, etc. His thesis is that any system that is (a) complex and (b) tightly coupled will always have accidents, so that the accidents should not be considered as abnormal but rather as normal. The same applies to biological systems.
0 Knew: Homeostasis helps to achieve stability in the body.
ReplyDelete1 Learned: There is a level of "coupling" that exists between organs, and an "uncoupling" can be a product of disease of aging.
2 Pressing: What is meant exactly by organs being "coupled"? When building a human-on-a-chip, how coupled do we want our organs? What if we need to test a disease state... do we need to alter how/ to what extent our organs are coupled?
3 Presentation: Organ coupling and disease: how organs are coupled
4 Thoughts: A good timeline of how systems biology has developed from physiology and the reductionist approach. Would like to discuss organ coupling more. What exactly is Human Physiome Project and is it useful to us?
SysBio13 Asgn_7B_Class_07_Article_16_2013_09_12
ReplyDelete0. Knew: Concept of networks (from discussion in class) and homeostasis.
1. Learned: The importance of coupled organs in maintaining a healthy dynamic stability. Fluctuation has been found to be healthy within a bound, and if no variability is seen, it is likely the system is not robust.
2. Questions: So, can you say that physicians adjusting such properties as blood pressure and pH are intervening and being counterproductive? Does altering the patients "negative" state keep the body from recognizing the signals of trouble and naturally adjusting?
3. Presentation: sympathetic and parasympathetic systems and control
4. Thoughts: Very interesting article. Brings up the need to discuss how one can create these self-correcting networks in a HoC since the organs are not as interconnected as in an actual human. What level of coupling is needed for HoC?
David Wooten
ReplyDeleteSysBio13 Asgn_7B_Class_07_Article_16_2013_09_12
0. Knew: A lot of the history of systems biology, and many of the concepts discussed.
1. Learned: How complex the inflammation response is! Also about ApEn and cross-ApEn.
2. Pressing ?: How physiological systems communicate to coordinate a response (physically and conceptually)
3. Presentation: Synergetics
4. Thoughts: Fun article to read! It was fascinating learning the history of physiology and homeostasis, and how it's much more complicated than it seems.
0. Knew: homeostasis is essential to proper biological function. Concept of homeostasis arising from system components.
ReplyDelete1. Learned: ApEn calculation to determine correlation between system components.
2. Pressing ?: How commons is MODS? How are physicians preventing it?
3. Presentation: Applying ApEn to microfluidic coupling / scaling of organs.
4. Thoughts: Well-written. ApEn seems like a valuable tool.
0. Knew: External control of an intracellular environment is as hard as it sounds.
ReplyDelete1. Learned: Highlights necessity for integration of data collecting , exponential and scale-free networks, Important distinction between disruption via either a specific mechanism or the connectedness among components, grandpas aren’t maladaptive, their responses are just inadequate, predictive vs representative modelling.
2. Pressing: Modelling of MODS in OoC’s? Would looking into how the dysfunction of communication between organs produce a net gain in understanding organ relationships as opposed to getting these OoC’s as physiologically close to their real counterparts?
3. Presentation: Physiological applications of different types of noise and what they mean
4. Thoughts: The history of system analysis was cool, going back to the idea of attractive wells in homeostasis. Detailing of inflammatory response was a good example of a systemic reaction to a perturbation.
0. Knew: A little about systems biology, physiology, and network structure.
ReplyDelete1. Learned: Using ApEn and cross-ApEn to estimate coupling. The principle of tightening the coupling between independent signals and random components to increase the stochastic behavior.
2. Pressing: How can we use applied stochastic resonance for HoC? How much of this process do we have to understand to build an effective HoC?
3. Presentation: Beneficial Noise
4. Thoughts: When we're setting up the network structure for OoC/Hoc how are we going to deal with the connections between molecules, cells, tissues, and organs?
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ReplyDeleteJPW