Read Article 08 P. R. LeDuc, W. C. Messner, and J.
P. Wikswo. How do control-based approaches enter into biology?
Annu.Rev.Biomed.Engr. 13:369-396, 2011. This article addresses a problem
central to much of existing biology, systems biology, and organs on a
chip -- much of the work to date has been done in an open-loop manner,
and hence does not adequately probe the system dynamics. Post a PCRC on
the Blog.
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) KNEW
ReplyDeleteI read this article last year, so I was pretty familiar with the ideas of black box, grey box, and clear box. I also knew about PID control. I knew of the distinction between open loop and closed loop control.
1) LEARNED
We can use optogenetics to control ion channels. ECM and shear stress are important inputs to a cell. A positive feedback circuit was created in E. coli using mutant T7 RNA polymerase. IM-MS will be pivotal in closed loop approaches.
2) QUESTION
How will we be dealing with ECM adhesions in our chip? Could patch clamping our "faked" ENS be helpful?
3) PRESENTATION
Linearization techniques with grey box control
4) THOUGHTS
I liked reading back through this. I certainly gained some more insights this year. I need to look into some of the references that I highlighted, mostly those that were reviews of up-to-date controls of biology. There is a long way to go in biology before we have full closed loop control.
0) Knew: concepts of control loops, black, grey, and clear-box models.
ReplyDelete1) Learned: how proportional, derivative, and integral control methods provide dynamic feedback to a system based on error models. Also learned how these strategies coupled to black, grey, and clear-box models may be used in biology and their limitations.
2) Question: To what extent can closed-loop control be used in our proposed OoC system? Most of the input and output types discussed in this article require simpler setups than complex, co-cultured, in vitro models.
3) Presentation: we should go over our list of control IN and OF the MGLBA along with input and output types as discussed here, and the type of control and model necessary.
4) Thoughts: This was a good breakdown of control systems with examples and limitations in biology and biological models.
0) Knew:
ReplyDeleteI have some familiarity with feedback control, specifically positive and negative feedback in the endocrine and immune systems. Active immunity is heavily regulated by feedback control in regards to helper T, cytotoxic T, and B cell differentiation. In the endocrine system feedback control regulates things from water retention (ADH/Kidneys/posterior pituitary) to digestion.
1) Learned:
I learned about the different types of control (proportional, derivative, and integral). It was really interesting to learn that calcium homeostasis in both bone and intestine utilize both proportional and integral control. I also learned how different inputs like chemical, electrical, optical, mechanical and genetic input can be used to control the cellular environment that affects the cell response.
2)Question:
What metabolites or other localized factors can we establish in our GBLA model in order to control our GBLA-on-a-chip through chemical input?
3)Presentation:
Specific examples of chemical, mechanical, optical, electrical, and genetic input across the different regions of the GBLA
4): Thoughts:
This paper really helped me understand the fundamentals of control and how control functions in biological systems. It will be crucial for us to clearly outline the locations and methods through which we will use specific inputs to control our GBLA model.
0: Ideas of PID control, mechanotransduction, optical/electrical stimulation of neurons, other inputs/outputs, and open-loop vs. closed-loop control.
ReplyDelete1: Chemotaxi-based control, susceptibility of proportional control to steady-state error, the increased information cost of derivative control, and the advantages of the different implementations of PID controllers.
2: Which inputs and outputs would we consider? There will be a question of how invasive an input/output is and the efficacy of the controllability/observability.
3: Considerations of choosing a specific control/sensor. (Cost, efficacy, invasiveness, system perturbations,...)
4: Good overview of PID control in the context of biological systems and how different inputs and outputs can be used for them.
0) What I already knew
ReplyDeleteControl can be used to optimize stability and efficiency of various systems.
I gave a presentation on this paper with Louis and Gabby so I am familiar with the terminology.
1) What I learned
Refresher on the different types of inputs. Cells can be excited optically. Optical input is particularly interesting to me because usually fluorescent and luminescence are measured as outputs.
Biology is not Boolean, despite what we traditionally think of transcription factors being “on” or “off” based on levels of gene expression.
2) Most pressing questions
How do we pick which inputs and outputs to use to monitor a system? How do we know if we mistakenly think one output, for example a high level of gene expression, is caused by a particular input in multiple input single output scenarios?
3) Presentation topic
Real world examples of control theory being used in industry and their success in optimizing products
4) Thoughts
I really like this paper, it is a great overview of what control is and also philosophical in discussing how complicated biology is. I like learning about biology from different perspectives rather than how it is traditionally presented as memorizing tons of information.
0) What I Already Knew:
ReplyDeleteControl aims to drive systems to a certain functional point. It also can be used to garner further knowledge of a system.
1) What I Learned:
The main types of control functions: proportional, derivative, and integral. I also learned the advantages and disadvantages of these schemes and how combining them offers better control functions. Mechanical signals can play a large role in biological systems.
2) Questions:
How do we process the tremendous amount of data that biological systems could output in real-time? How do we filter out biological noise? How much of these control systems needs to be chemical and how much can be electrical/digital?
3) Presentation Topic:
Laser-tweezers. Noise filtration. Mechanical stimulation in biology.
4) Thoughts:
Good paper. Nicely tied together simple control theory with biological examples and future directions.