Dynamic Conditions
Dynamic Conditions - Related Videos
14:48
Generation of Dynamical Environmental Conditions using a High-Throughput Microfluidic Device
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Cited by 1 •
2021
We present a microfluidic system for high throughput studies on complex life machinery, which consists of 1500 culture units, an array of enhanced peristaltic pumps and an on-site mixing modulus. The microfluidic chip allows for the analysis of the highly complex and dynamic micro-environmental conditions in vivo.
04:17
Ex Vivo Placental Explant Flow Culture - Mimicking the Dynamic Conditions In Utero
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Cited by 2 •
2023
Here is a protocol for culturing placental explants under constant flow conditions. This approach enhances traditional static villous culture systems by enabling the replication of dynamic physiological environments.
06:46
Fear Conditioning
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2023
Fear Conditioning is a type of learning in which an association is established between a negative unpleasant event and a harmless stimulus. This leads to a fear of the harmless stimulus. This process is largely mediated by the amygdala, which is a brain region involved in emotions and stress reactions. Fear conditioning can be utilized in several ways to understand different aspects of learning and memory. This video presents an overview of the principles behind fear conditioning, discusses the...
10:18
Dynamic Pore-scale Reservoir-condition Imaging of Reaction in Carbonates Using Synchrotron Fast Tomography
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Cited by 6 •
2017
Synchrotron fast tomography was used to dynamically image dissolution of limestone in the presence of CO2-saturated brine at reservoir conditions. 100 scans were taken at a 6.1 µm resolution over a period of 2 h.
12:03
Dynamics of Structures
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2023
Source: Roberto Leon, Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA It is rare nowadays that a whole year goes by without a major earthquake event wreaking havoc somewhere around the world. In some cases, like the 2005 Banda Ache earthquake in Indonesia, the damage involved large geographic areas and casualties in the six figures. In general, the number and intensity of earthquakes is not increasing, however, the vulnerability of the built environment is...
FAQs
Dynamic conditions shape engineered systems by changing the inputs that cells experience over time. Variations in flow, mechanical loading, oxygen, nutrients, or biochemical signals can modify transport and cell signaling, which may then affect gene expression, growth, and tissue organization. These linked responses help explain why time-dependent experiments can produce behavior that constant environments do not capture.
Feedback between cells and their surroundings allows environmental changes and cellular responses to influence one another. A shift in flow, oxygen availability, nutrients, or biochemical signaling can affect cellular behavior, while that behavior can contribute to further changes in tissue organization and growth. Accounting for this interaction helps bioengineers interpret outcomes in systems designed to resemble living tissues.
Constant environments hold relevant parameters at fixed levels, whereas Dynamic Conditions expose cells or tissues to changing inputs. This distinction matters because transport, signaling, gene expression, growth, and organization may respond differently when conditions vary over time. Consequently, a dynamic platform can provide information about responses to changing physiological inputs that a constant setup may not reveal.
Researchers can regulate physical, chemical, and biological variables according to the behavior they want to reproduce. Examples include fluid flow, mechanical loading, oxygen availability, nutrient levels, and biochemical signals. These inputs may be applied in bioreactors, tissue-engineering platforms, organ-on-chip models, or cell cultures to create experimental environments that more closely reflect changing conditions in living tissues.
Changing inputs are useful when researchers need systems that represent the varying environments experienced by living tissues. Dynamic platforms support work on engineered tissues, disease models, and therapeutic strategies, while also helping assess how cells respond to altered transport, mechanical forces, oxygen, nutrients, or biochemical signals. Their value lies in providing more physiologically relevant experimental conditions than fixed environments.
In bioengineering, Dynamic Conditions can be incorporated into bioreactors, tissue-engineering platforms, organ-on-chip models, and cell cultures. These systems use changing physical, chemical, or biological inputs to study effects on signaling, gene expression, growth, and tissue organization. The resulting information can guide engineered-tissue design, support disease-model development, and inform therapeutic strategies that depend on tissue responses.