Meredith+L.

into embryotic-like cells (pluripotent), which allows them to become any new kind of cell. This experiment was successfully completed with mice, but in the future can hopefully be used on humans. This process is also very cheap and quick.



Pluripotent cells are cells which can develop into many different types of cells, different than totipotent because they do not develop into a complete organism. Pluripotent cells will develop into nerve cells, cells of different organs, tissue cells, etcetera.

Earlier experiments to reprogram cells into pluripotent cells involved fusing cells together to transfer their nuclei. With this process, genome-wide transcriptional activity and DNA methylation patterns were converted and the cells were reprogrammed into an embryotic state.

The process used now, named STAP (stimulus-triggered acquisition of pluripotency), which is to produce pluripotent cells from mature cells is so unique since there is no genetic manipulation. They become pluripotent by being stripped of their memory that makes them differentiated from one another. The researchers began with mature cells and let them multiply before applying stresses such as exposing them to trauma, low oxygen levels and acidic environments. The cells that survive these conditions (roughly 20%) by reverting back to their state which closely resembles embryonic stem cells (the pluripotent cell). However only 30% of the 20% in one experiment went on to being pluripotent. These numbers are still good results considering the usual 1% efficiency of creating iPS cells.

If this process works with humans, treatments will be available using the patients own cells which have been reprogrammed. This makes medicine personalized. This process offers a new technique to replace and repair damaged cells. It also offers a new way to create stem cells other than embryonic harvesting, which has ethical issues, or by using adult stem cells.

media type="custom" key="25229840"

Further Reading:
1) Miniature brains created from stem cells: [] 2) Attempts to regenerate hair follicles from stem cells (cure for baldness) [] 3) Skin cells transformed into liver cells [] 4) More information of Pluripotent stem cells []

Sources:
[] [] [] [] []

=__**Wikipost #2: The Evolution of the Human Brain**__=



Humans are known for having larger brains than what is expected of that size mammal. The modern human brain is the largest and most complex of any living primate. Over approximately 7 million years, the human brain has tripled in size and most of the evolution and growth has happened in the past 2 million years.

Since we have no ancient brains to compare todays brains to, we study ancients skulls and a few rare fossils that have preserved natural casts of the interior of skulls. By looking at these early skulls, we can see details about the volumes of ancient brains and the relative sizes of major cerebral areas. Traditionally, the volume of the skull is used to determine the size of the brain, but this is a slight overestimate since the braincase contains fluids and membranes in addition to the brain.

The size of human brains for the first two thirds of our history were the size of ape brains today (a volume between 400 and 550 mL). During these first two thirds of our history, the brain started to show subtle changes in structure such as the neocortex beginning to expand (reorganizing its function from visual processing to other regions of the brain).



During the third part of the evolution of the human brain, the brain grew and there was an expansion of a language-connected part of the frontal lobe. The oldest fossil skulls of Homo erects ( 1.8 million years ago) had brains with a volume around 600 mL. 500 000 years ago, brains reached more than 1000 mL in volume and early Homo sapiens had brains within the range of 1200 mL which is the same as today.

This evolution of the brain can be explained by the theory that as culture and linguistics became more complex, our brains adapted and evolved over time. The shape changes noticed in the brain are regions related to depth of planning, communication, problem solving and other advanced cognitive functions.

The earth's climate also fluctuated other past 3 million years, and these fluctuates increased the most during the time the brain evolved the most ( roughly 500 000 years ago). Developing a brain that could process new information would have been a huge advantage to surviving during these climate changes. Evolving to adapt to your environment is natural selection and survival of the fittest. Humans adapted to survive in their new environment by learning about it.

To understand how the brain functions : media type="youtube" key="9UukcdU258A" width="560" height="315" = = =**__Further Reading:__**=

1) understanding the layers of the brain better: __ [] __ 2) evolution of humans : __ [] __ 3) more on evolution/adaptation with climate change: __ [] __ 4) evolution of mammal brain: __ [] __

=**__Sources :__**= [] [] [] []

=__Wikipost #3: Neuroelectronics__=

Researchers in many locations are all striving for a similar goal: create a commuter based off of the human brain. The goal of this is to have a computer with three basic components of the brain that have that computers today do not. These include low power consumption since human brains use roughly 20 watts while supercomputers today use megawatts; fault tolerance (brains loose neurons all the time, computers do not have the same ability to loose microprocessors); and a lack of needing to be programmed (brains learn and change as they interact with new environments, unlike computers that follow strict pathways). At Stanford University, there is a group of researchers trying to create electronics based on the engineering of the brain. Because the brain is energy efficient and carries out complicated systems with only a mass of neurons, the computer chips being designed are inspired by human neurons.

To do this, the researchers are building systems of non-digital chips that have similar functions are the networks neurons create in the brain. So far, a device called Neurogrid has been created which emulates a million neurons (as much as a honeybee's brain). This technology, called neuromorphic technology, shows great promise for small electronics needing low power such as smartphones, robots, artificial eyes and ears.

Sub-threshold silicon, which is a circuitry that operates at voltages that are to small to flip a computer bit from a 0 to a 1, are used to mimic the brain and it's low powered processing. With the small voltages, there is a small trickle of electrons that run through the transistors. This trickle of electrons is very similar in both size and variability to the ions flowing through the channels in a neuron. The basic idea was to create tiny circuits that display the same electrical behaviour as neurons. The circuit neurons could be linked together by decentralized networks that function similarly to real neural circuits found in the brain. This means with communications lines that run between components, not a central processor.



A successful silicon neuron was shown to be a reality in the 1990s and that it would be able to accept outside electrical input through junctions that performed the roles of the synapse (which are the tiny structures where nerve impulses travel from neuron to neuron). The device allowed all incoming signals to accumulate voltage in the interior of the circuit. Once enough the amount of voltage passes the threshold, a silicon neuron is fired which produces a series of voltage spikes that travel out along the wires representing the axon.

These silicon neurons use minimal power and energy because, like the brain, they simply integrate inputs until they are fired unlike a computer which needs a constant flow of energy to function. These chips being created can solve complex problems while using only 1% of the power current chips are using.

To further explain how neurons communicate: media type="youtube" key="t_FLQS35oIU" width="560" height="315"

Sources:
[] [] [] []

Further Reading:
1) more on neuroelectronics: [] 2) Neuromorphic chips: [] 3) How neurons work: [] 4)