User:Matthew Czerwonka/Wiki Sandbox Assignment

Traumatic Brain Injury (TBI) Modeling attempts to replicate certain aspects of TBI in order better understand what is physically happening to the brain. A variety of models can be used for this process with different models able to replicate certain aspects of TBI while also producing their own limitations.

Introduction
There are an estimated 1.7 million cases of TBI per year, and does not take into account the lasting affects that TBI may cause. TBI is also reported to be a contributing factor in about 30% of all injury related death. Given how prevalent TBI is, preventing or minimizing its effects would benefit many people worldwide.

In order to better understand what is happening during TBI, models are used to approximate the damage. Models bring both advantages and disadvantages to TBI research; on one hand brain models are very good at representing one aspect that can be observed, while on the other, aspects of the whole system must be ignored. For example, when studying blunt impacts, a neuronal cell culture model can be created that is the depth of the cortical layer. This is then subjected to different impact sizes, shapes, and forces in order to see how the cells react and what cytokines are released. This model works very well for the cortical layer, but deeper cell layers must be ignored due to the inability to oxygenate a deeper cell culture effectively. Hence the disadvantage and limitation of this model is cell depth; any interactions that might occur below the cortical layer are ignored in order to gather accurate information within the cortical layer.

Damage on a Cellular Level
TBI occurs when neurons in the brain experience stresses and strains that exceed their threshold for elastic deformation (source). Once this threshold is passed, cells begin to die due to apoptosis, or simply from the rupturing of cell membranes. The death of neurons is compounded by the fact that neurons do not undergo mitosis unless very specific conditions are met; not only are the cells removed, but they are also not replaced by new neurons. This, in turn, means that a person experiencing multiple TBIs in a similar area will suffer the culmination of all previous injuries.

In addition to the physical stresses and strains that neurons experience during TBI, cell-cell interactions also contribute to the damage, primarily due to the formation of a glial scar. Neurons release cytokines during TBI that have a variety of effects, including summoning astrocytes to the afflicted area. Once they arrive, the astrocytes begin to generate more cytoskeletal structures until the damaged region is completely sealed. While this does create chemical and physical stability in the area, this scarring prevents any self-healing processes from occurring.

Blast-Induced
Blast-Induced TBI results from wave propagation from a blast source. These injuries are most commonly found on the battlefield, as explosions occur close enough to humans that the high intensity waves apply stresses and strains that greatly surpass neuron elastic thresholds. As the wave passes through the skull, cerebrospinal fluid, and through the brain, neurons undergo sequences of tension and compression for the duration of the blast wave. Even very short blast waves with high intensity can cause immediate cell death, even through the cerebrospinal fluid buffer. Blast-Induced damage is not localized to a specific region due to its wave nature, and can penetrate deep into the brain before finally subsiding, depending on the blast intensity and proximity.

Impact-Induced
Impact damage is the most common type of TBI, and results from the brain making physical contact with the skull. Impact-induced TBI is localized to the region of impact, although the depth varies by person and force of impact. While cerebrospinal fluid normally acts as a buffer between the brain and skull, during moments of extreme force (i.e. car collision or physical contact sports), this barrier can be overcome, resulting in an impact as the brain rams into the skull. During the moment of impact, some neurons die immediately from being crushed, while other neurons may be damaged to varying degrees and undergo apoptosis. Impact-driven TBI is estimated at 75% of all TBI injuries.

in vitro
in vitro models are the most versatile modeling method, due to any aspect of TBI being able to be analyzed, as long as the model is created to do so. in vitro models are very useful for measuring forces among neurons, as there is much more freedom of space and time to measure the forces, as opposed to trying to fit the sensors in the brain itself. Using in vitro models alone, however, will not give a complete understanding of TBI mechanisms, due to the specialization of each model. As the model becomes more and more specialized, general overarching effects that may be present in the live model are removed.

Many experiments have been conducted in attempts to create a general model for the mechanical tolerance of neurons within the Central Nervous System (CNS). One such in vitro model has found that CNS neurons have a lower threshold for stress and strain loads than Peripheral Nervous System (PNS) neurons.

in vivo
in vivo models are the opposite end of the spectrum. In these models, specialization is sacrificed in order to observe brain reactions in the context of the whole body. While this gives a better understanding of the reactions to TBI as a whole, in vivo models have many effects that are not solely due to the injury, which may cause a misattribution of the causes to effects that have nothing to do with the injury itself. In order to sort out the irrelevant effects, in vitro models are created to mimic what was found with the in vivo model. Running these iterations allows true causes and effects of TBI to be found, which in turn allows for future research to mitigate these causes and effects.

Difficulties and Limitations of TBI Modeling
The brain is the most complex and least understood organ in the body, resulting in modeling the brain as a whole virtually impossible with current technology. In order to compensate for this complexity, models for the brain must be explicitly defined as to what exactly they model. Doing this inevitably results in many well defined models for different parts of the brain. However, they are all taken out of context of the 'whole brain', meaning that brain models do not incorporate aspects such as spacial and depth characteristics that a whole brain would have to prevent damage.