13.20: Central Nervous System - Biology

The human brain. The "control center." What does it control?

Practically everything. From breathing and heartbeat to reasoning, memory, and language. And it is the main part of the central nervous system.

Central Nervous System

The nervous system has two main divisions: the central nervous system and the peripheral nervous system (see Figure below). The central nervous system (CNS) includes the brain and spinal cord (see Figure below). You can see an overview of the central nervous system at this link:

The two main divisions of the human nervous system are the central nervous system and the peripheral nervous system. The peripheral nervous system has additional divisions.

This diagram shows the components of the central nervous system.

The Brain

The brain is the most complex organ of the human body and the control center of the nervous system. It contains an astonishing 100 billion neurons! The brain controls such mental processes as reasoning, imagination, memory, and language. It also interprets information from the senses. In addition, it controls basic physical processes such as breathing and heartbeat.

The brain has three major parts: the cerebrum, cerebellum, and brain stem. These parts are shown in Figure below and described in this section.

In this drawing, assume you are looking at the left side of the head. This is how the brain would appear if you could look underneath the skull.

  • The cerebrum is the largest part of the brain. It controls conscious functions such as reasoning, language, sight, touch, and hearing. It is divided into two hemispheres, or halves. The hemispheres are very similar but not identical to one another. They are connected by a thick bundle of axons deep within the brain. Each hemisphere is further divided into the four lobes shown in Figure below.
  • The cerebellum is just below the cerebrum. It coordinates body movements. Many nerve pathways link the cerebellum with motor neurons throughout the body.
  • The brain stem is the lowest part of the brain. It connects the rest of the brain with the spinal cord and passes nerve impulses between the brain and spinal cord. It also controls unconscious functions such as heart rate and breathing.

Each hemisphere of the cerebrum consists of four parts, called lobes. Each lobe is associated with particular brain functions. Just one function of each lobe is listed here.

Spinal Cord

The spinal cord is a thin, tubular bundle of nervous tissue that extends from the brainstem and continues down the center of the back to the pelvis. It is protected by the vertebrae, which encase it. The spinal cord serves as an information superhighway, passing messages from the body to the brain and from the brain to the body.

Humanoid Robot Brains

The smartest people in the world have spent millions of dollars on developing high-tech robots. But even though technology has come a long way, these humanoid robots are nowhere close to having the "brain" and motor control of a human. Why is that? Learn about the motor control processes in the human brain, and how cutting-edge research is trying to implement it in robots below.


  • The central nervous includes the brain and spinal cord.
  • The brain is the control center of the nervous system. It controls virtually all mental and physical processes.
  • The spinal cord is a long, thin bundle of nervous tissue that passes messages from the body to the brain and from the brain to the body.


  1. Name the organs of the central nervous system.
  2. Which part of the brain controls conscious functions such as reasoning?
  3. What are the roles of the brain stem?
  4. Sam’s dad was in a car accident in which his neck was broken. He survived the injury but is now paralyzed from the neck down. Explain why.

T Cell Tolerance

00:00:08.05 So, my name is Diane Mathis.
00:00:09.25 I'm a professor of immunology
00:00:11.21 at Harvard Medical School.
00:00:13.21 My two talks have to do with
00:00:17.00 immunological tolerance,
00:00:18.25 in particular T cell tolerance.
00:00:22.05 In the first talk,
00:00:23.29 I'll relate some general concepts
00:00:26.17 and then go on to
00:00:29.23 define and describe the major mechanisms of tolerance.
00:00:33.17 And then in the second talk,
00:00:35.17 I'll focus on one particular mechanism
00:00:39.07 of enforcing tolerance.
00:00:42.19 So, some general concepts.
00:00:46.17 the major function of the immune system
00:00:49.15 is to fight off microbial challenges.
00:00:52.10 It does this by mobilizing its two major arms:
00:00:56.12 the innate response and the adaptive response.
00:01:00.05 The innate response comes in early
00:01:02.26 and it's quite stereotypic.
00:01:04.23 It's a hardwired system
00:01:08.09 that includes cells like macrophages and neutrophils.
00:01:13.01 The adaptive system. response
00:01:18.01 comes in a little bit later
00:01:20.00 and it's a more nuanced response.
00:01:22.10 The major players in the adaptive response
00:01:26.21 are B and T lymphocytes.
00:01:29.22 Now, these cells have, displayed on their surfaces,
00:01:33.26 receptors that are specific for particular antigens.
00:01:39.19 The B cell receptor, or BCR,
00:01:42.21 for B cells,
00:01:44.20 which is also called immunoglobulin,
00:01:47.05 and the T cell receptor, or TCR, for T cells.
00:01:50.23 Now, in general,
00:01:52.29 each B or T cell
00:01:55.29 has multiple copies of a receptor
00:01:59.03 that sees one particular antigen
00:02:01.21 or a group of structurally related antigens,
00:02:06.13 so you can understand that
00:02:08.10 in order to fight off the myriad of microbial challenges,
00:02:11.27 that the repertoire must be both big and diverse.
00:02:17.02 And this happens by
00:02:19.14 random rearrangement of gene segments
00:02:24.05 encoding variable regions of the T and B cell receptors
00:02:27.27 as these cells are differentiating,
00:02:32.00 in the thymus for T cells
00:02:33.24 and in the bone marrow for B cells.
00:02:38.16 Now, since it is a random process,
00:02:41.28 just by chance,
00:02:44.11 sometimes specificities will be generated
00:02:46.27 that are able to recognize
00:02:49.08 the body's own constituents.
00:02:51.05 For example, a T cell may see insulin
00:02:55.07 or it may see the acetylcholine receptor,
00:02:59.05 or it may see myelin basic protein,
00:03:01.23 and if these T cells are let loose
00:03:05.05 they would cause autoimmune attack on the pancreas,
00:03:08.20 or myasthenia gravis,
00:03:10.24 or multiple sclerosis,
00:03:13.20 which is an autoimmune attack in the central nervous system.
00:03:17.21 Now, since this is
00:03:20.08 a very dangerous problem for the individual,
00:03:22.29 through evolution,
00:03:25.09 multiple levels of immunological tolerance
00:03:29.23 have come into play.
00:03:32.24 Now, these are generally
00:03:35.28 divided into central and peripheral mechanisms.
00:03:39.12 Central tolerance has to do with
00:03:42.16 the primary lymphoid organs
00:03:44.15 where T cells or B cells are generated,
00:03:46.08 so, for T cells, in the thymus.
00:03:48.25 So, the antigens that would be dealt with
00:03:51.17 in central tolerance
00:03:53.07 would be antigens that are expressed in the thymus
00:03:56.19 or are expressed in all cells,
00:03:59.03 or are expressed in cells which are
00:04:02.16 trafficking through the thymus,
00:04:04.00 like blood cells, for example.
00:04:06.08 Peripheral tolerance has to do with those cells,
00:04:11.05 once they've emerged from the thymus
00:04:13.15 and are now in the periphery,
00:04:15.16 and can see potential self-antigens
00:04:19.04 in the liver or in the heart or in various tissues.
00:04:25.19 Now, the major mechanisms of central tolerance are:
00:04:30.05 first, clonal deletion,
00:04:31.28 which is physical removal of that particular T cell from the repertoire
00:04:38.12 clonal inactivation,
00:04:42.09 where the T cell is there,
00:04:44.21 but once it gets into the periphery
00:04:47.07 it's no longer able to make a response
00:04:51.17 and then clonal diversion,
00:04:53.27 the T cell is there and it can respond,
00:04:55.21 but during its differentiation
00:04:58.21 it gave up its identity as an effector T cell,
00:05:03.04 which is the kind of cell
00:05:05.26 which actually does the damage,
00:05:08.06 and has taken on the mantle
00:05:10.23 of another kind of cell, a regulatory cell.
00:05:14.19 The mechanisms of peripheral tolerance
00:05:16.29 are somewhat similar.
00:05:19.07 So, the first three are the same
00:05:21.08 -- deletion, inactivation, and diversion --
00:05:22.23 but onto this are added three more.
00:05:25.21 So, clonal ignorance just refers to the fact that
00:05:29.19 some T cells can escape,
00:05:31.07 but they're quite fine,
00:05:33.02 because the antigen that they see
00:05:35.00 is hidden from the lymphocyte circulation.
00:05:39.18 So, for example, it might be an antigen
00:05:42.02 which is in a cell
00:05:43.27 that's behind the blood-brain barrier
00:05:45.09 or it might be an antigen
00:05:47.06 which is in the eye,
00:05:48.18 which is thought to be "immune privileged",
00:05:52.10 or an antigen which is in the testis.
00:05:54.00 So, normally, these are not seen
00:05:55.26 unless there's some kind of damage
00:05:58.16 to these different tissues,
00:06:00.16 which releases the antigen into the circulation.
00:06:03.22 Helplessness refers to the fact that
00:06:06.07 many B cell and cytotoxic T cell responses
00:06:12.01 must have help from CD4+ helper cells
00:06:17.16 in order to respond effectively.
00:06:19.20 So, as you can imagine,
00:06:21.25 you might not need to directly
00:06:24.15 tolerize that B cell or that cytotoxic T cell,
00:06:26.13 but rather the CD4+ T cells
00:06:29.09 that are helping them.
00:06:31.21 And then, finally, suppression,
00:06:36.22 which is a major mechanism,
00:06:39.02 refers to the fact.
00:06:39.17 refers to cells which keep in check the activity
00:06:42.10 of effector T cells.
00:06:46.19 So, looking at that net of mechanisms
00:06:51.25 which I showed you,
00:06:53.00 you might be tempted to think that
00:06:55.27 this is very comprehensive
00:06:57.27 and autoimmunity should be rare.
00:07:01.10 But, breaks in tolerance do occur,
00:07:02.24 leading to autoimmunity
00:07:04.12 and, in the most extreme form,
00:07:06.22 to autoimmune disease,
00:07:08.13 and they occur quite often
00:07:12.10 -- 5-8% of the population in Western countries
00:07:16.22 have some form of an autoimmune disease --
00:07:21.03 and they occur by different means.
00:07:23.22 So, at the last calculation,
00:07:26.04 there are more than 80 different types
00:07:28.29 of autoimmune diseases,
00:07:30.25 and probably double that
00:07:34.17 because sometimes we lump together
00:07:36.19 a particular autoimmune disease
00:07:39.00 just because they have the same manifestations,
00:07:41.10 for example, arthritis,
00:07:43.15 but the way to get there might be,
00:07:45.09 actually, quite different.
00:07:48.12 So, let's look a little bit more closely
00:07:51.19 into central tolerance.
00:07:53.22 And I'd like to focus on the first mechanism that I mentioned
00:07:59.09 -- clonal deletion.
00:08:01.02 Now, as I said,
00:08:02.19 clonal deletion is physical removal
00:08:04.09 of the self-reactive T cells from the repertoire,
00:08:07.24 and this is a quite important mechanism
00:08:12.14 because fully two-thirds of the T cells
00:08:16.08 that reach full maturity in the thymus
00:08:19.00 actually undergo clonal deletion,
00:08:22.04 because they have some self-reactivity.
00:08:24.27 And it's also the most definitive mechanism
00:08:26.18 because it ends in death,
00:08:28.04 and you can't be more definitive than that.
00:08:32.11 So, I'd like to tell you
00:08:37.22 more about this mechanism of clonal deletion,
00:08:40.22 but before I do that
00:08:43.04 I have to explain to you
00:08:44.28 how T cells see antigen
00:08:46.26 and how they differentiate in the thymus.
00:08:49.20 So, a T cell actually sees its antigen quite differently
00:08:52.25 from how a B cell sees its antigen.
00:08:56.04 B cells see antigens through their B cell receptor,
00:09:00.29 or immunoglobulins,
00:09:02.10 very directly.
00:09:03.20 They actually recognize
00:09:06.11 a piece of the three-dimensional structure
00:09:09.02 and then make a response.
00:09:11.02 For T cells, it's quite different.
00:09:13.20 They must recognize
00:09:16.09 a short peptide sequence,
00:09:18.12 a primary sequence,
00:09:20.23 presented by major histocompatibility complex molecules,
00:09:27.02 which occur at the surface of most cell types.
00:09:32.01 Now, this presentation of antigens to T cells
00:09:36.06 is a quite complicated
00:09:38.22 and very elegant mechanism,
00:09:40.04 which, if you're interested in,
00:09:43.02 you can refer to the talk by Dr. Mellman,
00:09:46.09 which goes into much more detail.
00:09:49.01 But, suffice it to say, in this context,
00:09:51.14 an antigen would be either
00:09:54.09 synthesized by a cell or taken up by a cell,
00:09:57.12 and then undergoes proteolytic degradation
00:10:01.00 to make peptides.
00:10:02.14 And according to where that peptide
00:10:04.26 was actually made,
00:10:06.06 and what enzymes were involved,
00:10:07.23 as well as the primary sequence of the peptide,
00:10:10.23 it can bind either to an MHC class II molecule
00:10:15.16 or an MHC class I molecule.
00:10:17.14 And then these molecules
00:10:21.26 shuttle the peptides to the surface.
00:10:23.26 Now, some T cell receptors
00:10:26.04 can see a peptide
00:10:29.29 in the context of an MHC class II molecule,
00:10:34.20 and it does this with the help of the CD4 co-receptor,
00:10:37.11 and these T cells turn out to be
00:10:40.10 CD4+ helper T cells.
00:10:43.07 Other T cells have receptors
00:10:45.11 that are capable of recognizing
00:10:47.16 MHC Class I molecules
00:10:49.17 and peptides within them,
00:10:51.16 and they're helped along with the co-receptor CD8,
00:10:55.26 and these cells turn into
00:10:57.29 CD8+ cytotoxic T cells.
00:11:01.26 Now, as I mentioned,
00:11:03.23 T cells undergo differentiation in the thymus.
00:11:07.05 The precursor, which gives rise to a T cell,
00:11:09.28 comes from the fetal liver
00:11:12.25 or the adult bone marrow,
00:11:14.24 and these precursors are really very ignorant.
00:11:19.27 So, they must go through a number of processes in the thymus
00:11:22.27 to educate them,
00:11:26.07 they must learn their antigen specificity
00:11:29.08 -- and they do this by rearrangement of the T cell receptor genes --
00:11:35.00 they must have an enrichment for T cells
00:11:37.13 which are able to see the MHC molecule
00:11:39.23 that the individual is expressing,
00:11:43.02 but not see it so well
00:11:47.06 that it might cause autoimmunity.
00:11:49.15 So, these are positive selection
00:11:51.02 and negative selection events.
00:11:53.14 And then, finally,
00:11:55.24 phenotypic specialization takes place.
00:11:59.08 So, I mentioned that there are CD8+ cytotoxic T cells
00:12:02.19 and CD4+ helper T cells,
00:12:04.27 and these are what we call effector cells,
00:12:07.06 which get the job done in an immune response.
00:12:11.02 There are also CD4+ regulatory T cells,
00:12:14.01 which control the activities of these effector cells.
00:12:19.14 Now, this all takes place in the thymus
00:12:22.00 by an orchestrated series of events.
00:12:27.17 The precursors enter through the blood vessels
00:12:32.23 at the corticomedullary junction,
00:12:35.25 and then they percolate through the cortex
00:12:38.25 and the medulla,
00:12:40.20 coming into contact with various stromal cell types
00:12:43.29 that express MHC molecules
00:12:48.05 with peptide at their surface,
00:12:49.15 and also produce different cytokines
00:12:53.02 and have different other types of receptors on their surface.
00:12:56.29 And through this series of contacts,
00:13:00.24 these different processes,
00:13:03.09 which are so important for the life of the T cell,
00:13:06.24 take place.
00:13:08.15 Now, it's possible to monitor this
00:13:10.28 using flow cytometry,
00:13:12.08 using the CD4 and CD8 co-receptors
00:13:16.12 as markers of the differentiation pathway.
00:13:20.19 So, when the precursor enters from the blood,
00:13:24.19 it doesn't express either CD4 or CD8,
00:13:29.16 and during this early time period
00:13:32.08 it's basically undergoing cell division
00:13:36.13 and is starting gene rearrangement.
00:13:40.06 Now, all of this takes place inside the cortex.
00:13:45.25 Now, eventually, CD4 and CD8 are both turned on,
00:13:50.13 to have the double-positive stage,
00:13:52.23 which also takes place in the cortex.
00:13:55.18 Now, immunoglobulin.
00:13:57.23 sorry, T cell receptor gene rearrangement
00:14:00.15 is completed
00:14:03.01 during this double-positive stage,
00:14:05.12 and these cells are then
00:14:07.17 ready to be positively and negatively selected.
00:14:12.17 If they're positively selected
00:14:15.12 and deemed worthy of final maturation
00:14:19.07 they become either CD4 single-positive,
00:14:22.02 if they saw an MHC class II molecule with peptide,
00:14:24.18 or CD8+,
00:14:26.27 if they saw an MHC class I molecule with peptide.
00:14:29.02 And this final step of differentiation
00:14:33.04 happens as the cells are entering the medulla.
00:14:36.11 So, the fate of a differentiating T cell
00:14:42.28 is very much focused on these molecules
00:14:45.15 that I've portrayed here
00:14:47.11 -- the interaction between the T cell receptor and co-receptors,
00:14:52.00 and the MHC molecules.
00:14:55.03 And it has to do with
00:14:58.06 the affinity of this interaction
00:15:00.12 -- so, how strongly the T cell receptor can see this complex --
00:15:04.21 and the avidity
00:15:07.00 -- how many T cell receptor and MHC complexes
00:15:09.14 actually become engaged on a particular set of cells?
00:15:15.26 So, with the least amount of interaction,
00:15:22.18 so, no interaction,
00:15:24.15 or with the strongest interaction,
00:15:26.13 death is the outcome.
00:15:30.00 So, with little interaction, the cell with die because of neglect
00:15:32.20 -- it doesn't get any signaling --
00:15:34.23 within three days of becoming a double-positive cell.
00:15:39.19 Now, with very strong interaction,
00:15:43.10 clonal deletion will take place,
00:15:45.11 and that cell is removed from the repertoire.
00:15:48.24 Now, with a signal that's a little bit stronger,
00:15:50.22 that's quite weak,
00:15:52.28 but stronger than nothing,
00:15:54.28 naive T cells will
00:15:58.23 continue maturation and eventually leave the thymus.
00:16:01.21 And these will be
00:16:04.02 both CD4 and CD8-positive T cells,
00:16:06.03 depending on whether the MHC molecule
00:16:08.19 was class I or class II.
00:16:11.05 And then somewhere between
00:16:13.22 the naive T cell and clonal deletion,
00:16:16.06 there's clonal diversion,
00:16:18.02 and that signal leads to
00:16:21.04 the changing of the effector T cell phenotype
00:16:24.09 to a regulatory T cell,
00:16:26.15 as I've described before,
00:16:27.26 or perhaps a cell which gets
00:16:30.18 shunted off to the intestine,
00:16:32.02 where it's rather innocuous.
00:16:37.11 So, I'd like to show you
00:16:39.22 some examples of clonal deletion,
00:16:42.24 and the most striking ones come
00:16:45.27 from T cell receptor transgenic mice.
00:16:47.22 So, unfortunately, any particular T cell specificity
00:16:51.06 is very rare in an individual
00:16:54.03 -- it's usually only 1 in 10^4
00:16:56.25 to 1 in 10^6 T cells
00:16:59.21 are of one particular specificity.
00:17:03.23 That means that that T cell receptor sees a particular antigen.
00:17:07.09 And that's very difficult to study and follow these cells,
00:17:09.28 so the trick that immunologists play
00:17:12.15 is to take a T cell clone,
00:17:15.20 which they know the specificity for
00:17:17.25 and they know where it came from,
00:17:19.11 and they take the already rearranged T cell receptor genes
00:17:24.01 from that T cell clone,
00:17:25.13 and use those to make transgenic mice with.
00:17:28.13 And since those are already rearranged,
00:17:30.07 they shut down endogenous rearrangement,
00:17:32.14 and you end up with a transgenic mouse
00:17:35.07 where the repertoire is highly skewed
00:17:37.22 for that transgene-encoded T cell receptor.
00:17:42.19 So, in one case, umm.
00:17:45.11 investigators started with a T cell clone
00:17:48.15 that was CD8+
00:17:53.20 and recognized an antigen which is male-specific,
00:17:56.04 and that's called the H-Y antigen
00:17:58.16 because it's encoded on the Y chromosome.
00:18:01.17 And they took those T cell receptor genes
00:18:03.14 and made TCR transgenics,
00:18:05.23 and they looked at differentiation in the thymus.
00:18:09.23 And what they saw, at steady state,
00:18:11.13 was that, yes, you get double-negatives,
00:18:14.15 as expected,
00:18:15.24 you get double-positives,
00:18:17.15 and then the single-positives are primarily CD8+,
00:18:21.08 because the clone that you started with was a CD8+ T cell.
00:18:25.07 Now, this is in females,
00:18:26.16 where the H-Y antigen does not exist.
00:18:29.27 If instead, you look in males
00:18:32.09 that are TCR transgenic,
00:18:33.23 what you find is you get double-negatives and you don't see any other T cells after that
00:18:40.02 -- they've been clonally deleted.
00:18:42.03 Now, another example
00:18:46.01 comes from a T cell clone that is CD4+
00:18:47.23 and it sees an antigen
00:18:50.17 which is found in the blood,
00:18:52.29 and it's called the C5 antigen.
00:18:54.26 It's a complement protein.
00:18:57.16 And when people make these T cell receptor transgenics,
00:19:00.29 in a line of mice
00:19:03.19 that naturally does not have C5,
00:19:05.27 they find that there are double-negatives,
00:19:08.09 double-positives,
00:19:09.14 and primarily CD4 single-positive cells.
00:19:12.12 However, if instead, they looked on a line
00:19:16.04 where C5 does exist,
00:19:18.18 they find double-negatives and double-positives,
00:19:22.02 but not CD4 single-positives.
00:19:25.03 Now, from this one slide,
00:19:26.26 you can already learn several things
00:19:28.19 about clonal deletion.
00:19:30.13 First of all, clonal deletion
00:19:34.02 happens to both CD4+ and CD8+ T cells.
00:19:38.06 And then, secondly, it can occur in different places
00:19:41.24 at different stages
00:19:43.17 during T cell differentiation.
00:19:45.06 So, in the top case,
00:19:47.24 we had an antigen which is male-specific,
00:19:50.16 and it's a ubiquitous antigen found on all cell types.
00:19:54.03 So, as soon as T cells. as double-positives turned.
00:19:59.04 have finished the rearrangement of their T cell receptors,
00:20:01.16 they get deleted,
00:20:02.26 and there's no T cells available for continuing with maturation.
00:20:08.09 It's a different case with this C5 antigen,
00:20:10.26 which is found in the blood,
00:20:12.14 because blood circulates through the thymus,
00:20:15.10 in the medullary region
00:20:17.20 and not in the cortical region,
00:20:18.23 and so double-positives never see this antigen
00:20:21.28 and it's only when the T cells are fully mature
00:20:25.15 and move into the medulla
00:20:26.28 that clonal deletion occurs.
00:20:28.27 In fact, clonal deletion can even occur
00:20:31.28 in the periphery under certain conditions.
00:20:38.14 So, the mechanism of clonal deletion is apoptosis,
00:20:43.25 and I think this is nicely shown
00:20:47.20 by the experiment illustrated on this slide.
00:20:49.06 So, here, people are
00:20:52.06 dealing with a T cell whose receptor
00:20:56.00 sees a quite common antigen
00:20:58.07 and sees it in the medulla.
00:21:01.26 And what they find.
00:21:03.19 and the way they look for clonal deletion
00:21:05.28 is to use what's called the TUNEL assay,
00:21:08.23 which is an assay which radioactively labels
00:21:11.04 free DNA ends,
00:21:13.09 which are generated during the process of apoptosis.
00:21:18.29 And so you can see, at the top,
00:21:21.07 when the antigen is present,
00:21:23.00 that there's a lot of apoptosis occurring in the medulla.
00:21:27.21 a little bit in the cortex, but mostly in the medulla.
00:21:29.08 however, when the antigen is absent,
00:21:31.12 you don't see these apoptotic structures.
00:21:39.15 As an example of how important
00:21:43.03 clonal deletion can be,
00:21:44.16 one should recognize the fact that
00:21:48.18 there are human autoimmune diseases
00:21:50.27 which reflect deficits in clonal deletion.
00:21:56.06 So, in one example,
00:21:58.05 there's a mutation in a transcription factor
00:22:01.04 which is important as a general
00:22:07.03 effector of immunological tolerance,
00:22:11.00 and so what happens is that
00:22:13.14 these individuals get a multi-organ autoimmune disease
00:22:16.07 called autoimmune polyglandular syndrome type-1.
00:22:20.02 In the second example,
00:22:22.03 it's a quite specific deficit
00:22:24.20 in central tolerance,
00:22:26.14 having to do with expression of the insulin gene
00:22:29.21 in the thymus,
00:22:31.24 and these individuals
00:22:34.26 specifically develop type-1 diabetes.
00:22:36.29 Now, the first example
00:22:39.11 will form the basis of my second talk,
00:22:42.06 so I won't go any further on that now,
00:22:45.11 but I will give you a little bit of information,
00:22:48.11 more information about the second example.
00:22:52.29 So, people have done a number of genetic studies
00:22:55.21 and identified several genes
00:23:00.11 which predispose to the development of type-1 diabetes in humans,
00:23:04.18 or protect from the development of type-1 diabetes.
00:23:09.05 Now, the most important one of these genes
00:23:11.15 is the HLA locus,
00:23:14.11 which is the equivalent of the MHC gene,
00:23:15.29 which I introduced you to.
00:23:17.29 But the second most important
00:23:20.00 is actually the insulin gene itself.
00:23:22.03 Now, the variation in
00:23:25.15 the diabetes-predisposing
00:23:28.00 versus the diabetes-protective insulin gene
00:23:31.23 is not in the coding region of the insulin gene,
00:23:35.15 but rather in the promoter region,
00:23:38.08 where there's a class of sequences
00:23:41.15 called variable number of tandem repeats
00:23:45.14 -- just a bunch of repeated sequences --
00:23:48.07 and depending on how many of these sequences
00:23:51.28 there are in the promoter region,
00:23:53.10 the allele is either
00:23:56.29 diabetes-promoting or diabetes-protective.
00:23:59.19 So, when there are just a few of these repeats,
00:24:01.17 it's diabetes-promoting,
00:24:03.01 and when there are more
00:24:05.22 it's diabetes-protective.
00:24:07.12 So, if we look through the population at these alleles
00:24:11.08 that have either protective or promoting VNTRs,
00:24:15.03 what we find is that those people who have the protective.
00:24:22.15 the promoting allele, the predisposing allele,
00:24:25.12 develop diabetes much more commonly
00:24:28.08 than the population in general.
00:24:32.00 And those are the examples on your left.
00:24:36.10 Now, the ones on your right
00:24:38.03 are those individuals who have
00:24:40.04 two copies of the protective allele,
00:24:42.14 and you can see that they develop diabetes
00:24:44.26 much less frequently than the general population.
00:24:49.04 And then, if you look to see
00:24:53.17 what these variations in the promoter regions
00:24:56.28 do to insulin gene expression,
00:24:58.17 what you find is that
00:25:01.06 there's not much difference in the expression of insulin
00:25:04.14 in the pancreas.
00:25:05.25 Where there is a big difference
00:25:07.11 is actually in expression of insulin
00:25:10.06 in the thymus.
00:25:11.18 And people have made the speculation
00:25:18.02 that those cases where there's higher expression,
00:25:22.00 for example, with the class III alleles,
00:25:24.27 these people have more expression of insulin,
00:25:28.26 greater clonal deletion in the thymus,
00:25:31.18 and then less development of autoimmunity.
00:25:34.11 And this has actually been modeled in mice
00:25:37.19 by making transgenic mice
00:25:40.06 which are expressing the different types of human alleles,
00:25:44.09 and the results fit very well this idea.
00:25:49.20 So, I hope I've convinced you by now that
00:25:53.22 central tolerance, and in particular clonal deletion,
00:25:55.11 is an important mechanism of immunological tolerance.
00:25:59.05 However, clonal deletion is never complete.
00:26:03.26 There are antigens which are not expressed in the thymus
00:26:07.02 or they're not expressed.
00:26:11.15 there are antigens which T cells don't see
00:26:13.28 with a high enough affinity,
00:26:15.15 or there are antigens whose concentration in the thymus
00:26:19.15 is not high enough to permit clonal deletion.
00:26:23.12 And one might actually make the statement
00:26:28.00 that it would be devastating
00:26:29.25 if clonal deletion was actually complete,
00:26:33.15 because, as you can imagine,
00:26:35.04 if you deleted all the T cells that saw any antigen
00:26:39.17 with any affinity
00:26:43.02 that there would be a very small repertoire
00:26:45.02 that would emerge into the periphery,
00:26:47.08 and not be able to fight off
00:26:49.09 the millions and millions of microbes
00:26:51.25 that the individual is going to encounter.
00:26:56.03 So, that leaves open
00:26:59.26 the space for peripheral T cell tolerance.
00:27:05.14 And I'm going to focus on one particular and important mechanism
00:27:09.23 of peripheral tolerance,
00:27:11.16 and that's suppression.
00:27:13.28 And, as I mentioned, suppression
00:27:17.28 is regulation of the behavior of self-reactive T cells
00:27:20.28 by other T cells. by other cells.
00:27:24.04 This is, again, an important mechanism,
00:27:27.01 and that can be seen very clearly
00:27:30.19 by the phenotype of either humans of mice
00:27:36.04 who are lacking a particular kind of regulatory T cell,
00:27:39.21 a suppressor T cell,
00:27:43.04 and these people get a very severe
00:27:45.13 autoinflammatory disease.
00:27:47.14 And, in fact, there are
00:27:49.14 more than just this type of suppressor cell
00:27:53.14 that keep effector T cells in check.
00:27:58.17 There are actually several types:
00:28:00.10 T cells
00:28:02.19 some people think some B cells suppressor cells
00:28:04.15 and also some macrophage suppressor cells.
00:28:08.15 But I'm going to focus my comments
00:28:11.06 on one very famous regulatory T cell,
00:28:14.16 the most famous T cell in immunology, actually,
00:28:18.11 and these are regulatory T cells
00:28:21.13 which express the transcription factor Foxp3,
00:28:24.11 and we call them, affectionately,
00:28:27.04 Treg cells.
00:28:28.23 So, these T cells express
00:28:31.24 the αβ T cell receptor,
00:28:33.17 the CD4 co-receptor,
00:28:34.19 and they express high levels
00:28:37.12 of the high-affinity receptor for IL-2,
00:28:42.10 and this molecule is called CD25,
00:28:45.07 and that was used for many years
00:28:47.18 as a means to distinguish them from other types of T cells.
00:28:50.21 But later, it was found that
00:28:53.16 these T cells are actually a particular lineage of T cells
00:28:56.18 and what defines that lineage
00:28:58.27 is the transcription factor Foxp3.
00:29:01.13 Now, normally circulating through the body
00:29:07.12 of just a standard person or mouse,
00:29:10.02 around 5-15% of the CD4+ T cells
00:29:14.23 are these Foxp3+ regulatory T cells.
00:29:18.19 And they're importance became very clear
00:29:21.24 when it was understood that
00:29:24.20 humans that have the IPEX disease,
00:29:27.08 and mice that have the Scurfy disease,
00:29:30.12 have a very severe autoinflammatory disease
00:29:35.01 affecting many organs,
00:29:36.13 because they are missing Foxp3
00:29:39.24 -- they have a mutation in it --
00:29:41.14 and sub.
00:29:43.20 consequently they are missing this population of regulatory T cells.
00:29:48.12 Now, as I mentioned,
00:29:49.26 these T cells are generated.
00:29:54.17 most of them are generated in the thymus
00:29:56.21 by the process of clonal diversion.
00:30:00.12 In other words, their T cell receptors
00:30:03.03 see a self-antigen expressed in the thymus
00:30:07.13 at an intermediate affinity
00:30:10.12 between what a naive T cell sees
00:30:13.10 and allows it to undergo maturation,
00:30:16.20 and a clonally-deleted T cell
00:30:22.27 that undergoes negative selection sees.
00:30:25.21 By now, using gain-of-function and loss-of-function experiments,
00:30:29.24 it's been determined that
00:30:32.23 Tregs actually control almost all types of immune responses.
00:30:36.26 They control autoimmune diseases
00:30:39.21 like inflammatory bowel disease or type-1 diabetes.
00:30:43.07 They control inflammatory diseases like rheumatoid arthritis,
00:30:47.14 allergic diseases such as asthma.
00:30:50.07 They also keep in check graft rejection.
00:30:53.28 They promote tumor escape,
00:30:58.12 and they inhibit the response
00:31:03.13 to various types of infections.
00:31:06.18 So, from graft rejection up,
00:31:10.20 the regulatory T cells are the good guys
00:31:13.25 -- the more you have, the less disease you have.
00:31:16.24 From tumors down,
00:31:19.18 the regulatory T cells are the bad guys,
00:31:22.04 so the more Tregs you have,
00:31:23.28 the less chance the individual has
00:31:27.09 of mounting an immune response against the tumor,
00:31:30.12 and the same thing for infections.
00:31:36.00 It was found that regulatory T cells,
00:31:41.17 as I've said,
00:31:44.05 are critical for controlling all types of inflammatory responses in the body,
00:31:49.25 and actually that this happens throughout life,
00:31:52.06 and that was determined by looking at mice
00:31:57.08 where it was possible to ablate regulatory T cells
00:32:03.04 by deleting the Foxp3 gene.
00:32:05.22 And so, if this was done from birth on,
00:32:09.25 it was very clear that the mice were very sick.
00:32:13.26 They died before 25 days of age
00:32:17.05 and they had a massive expansion
00:32:24.18 of immune cell populations
00:32:26.22 in the spleen and the lymph node,
00:32:28.22 and you can see in the bottom picture that they're actually quite small
00:32:31.25 and wasting away.
00:32:33.27 And in fact, you can wait
00:32:36.03 until the mouse becomes an adult,
00:32:38.04 and so it's had Tregs during this whole time,
00:32:40.28 and then just deplete Tregs
00:32:43.23 in an adult mouse,
00:32:45.09 and within a week or so
00:32:48.18 these mice will also develop
00:32:51.13 a very severe and fatal autoinflammatory disease.
00:32:57.08 More specifically,
00:32:59.07 Tregs will control particular types of autoimmunity,
00:33:02.00 and one nice example is the
00:33:05.19 development of type-1 diabetes in a mouse model
00:33:08.08 called the NOD mouse.
00:33:10.10 Now, when Tregs are there,
00:33:13.08 these Foxp3+ regulatory T cells,
00:33:16.14 autoimmunity does not develop
00:33:20.12 or it develops very slowly.
00:33:22.17 Whereas, if you get rid of Tregs,
00:33:26.16 it will develop much, much more quickly.
00:33:30.11 You can add in Tregs
00:33:34.09 and what you find is that these animals
00:33:36.20 that got diabetes really, really quickly
00:33:40.18 would now develop it much, much later,
00:33:45.18 off-scale on the timeframe that I'm showing you.
00:33:51.15 So. and then I'd just like to finish
00:33:54.21 by talking a little bit about the different effector mechanisms
00:33:57.13 that regulatory T cells use.
00:34:00.05 There are several.
00:34:02.19 One is by the production of anti-inflammatory cytokines
00:34:06.21 such as IL-10 or IL-35.
00:34:11.04 The second is by actually killing the effector T cell.
00:34:17.19 Third, they disrupt the metabolism of the cells,
00:34:23.13 for example,
00:34:25.19 I mentioned that regulatory T cells have
00:34:28.10 high levels of the high-affinity IL-2 receptor,
00:34:30.25 so they can act as a sink
00:34:34.12 for sucking up all this IL-2, which is actually required for the health
00:34:39.09 of the effector T cells.
00:34:41.24 And then, lastly, Tregs can
00:34:44.22 affect other types of cells,
00:34:46.23 antigen-presenting cells in the region,
00:34:49.09 and stop them from
00:34:54.22 triggering an immune response,
00:34:56.28 either by killing the cell or
00:34:59.08 changing what type of cytokines these cells make.
00:35:02.07 So, this is a quite complex mechanistic scenario
00:35:11.16 and people in the field have been asking,
00:35:14.04 is it the case that every single Treg cell
00:35:17.10 is able to do these different types of inhibition
00:35:22.22 and, if so,
00:35:26.16 when does one come into play and the other replace it?
00:35:29.00 Or it is that in any kind of Treg response,
00:35:33.04 there is a heterogeneous set of cells there,
00:35:37.22 some of which are specialized in doing mechanism 1
00:35:40.23 and others in doing mechanism 4
00:35:43.06 and others in mechanism 3?
00:35:45.05 And that's something which the field is very interested in
00:35:49.29 determining at the moment.
00:35:52.03 So, I'll just finish by saying that regulatory T cells
00:35:54.11 are a very exciting field at the moment in immunology,
00:35:59.06 that there's a lot of interest in
00:36:02.17 actually using them to control autoimmune diseases
00:36:07.00 or other inflammatory diseases
00:36:09.25 by taking them out, expanding them,
00:36:13.11 and reintroducing them into individuals with various diseases.
00:36:19.01 Thank you.

Autoregulation and multiple enhancers control Math1 expression in the developing nervous system

A.W. Helms, A.L. Abney, N. Ben-Arie, H.Y. Zoghbi, J.E. Johnson Autoregulation and multiple enhancers control Math1 expression in the developing nervous system. Development 15 March 2000 127 (6): 1185–1196. doi:

Development of the vertebrate nervous system requires the actions of transcription factors that establish regional domains of gene expression, which results in the generation of diverse neuronal cell types. MATH1, a transcription factor of the bHLH class, is expressed during development of the nervous system in multiple neuronal domains, including the dorsal neural tube, the EGL of the cerebellum and the hair cells of the vestibular and auditory systems. MATH1 is essential for proper development of the granular layer of the cerebellum and the hair cells of the cochlear and vestibular systems, as shown in mice carrying a targeted disruption of Math1. Previously, we showed that 21 kb of sequence flanking the Math1-coding region is sufficient for Math1 expression in transgenic mice. Here we identify two discrete sequences within the 21 kb region that are conserved between mouse and human, and are sufficient for driving a lacZ reporter gene in these domains of Math1 expression in transgenic mice. The two identified enhancers, while dissimilar in sequence, appear to have redundant activities in the different Math1 expression domains except the spinal neural tube. The regulatory mechanisms for each of the diverse Math1 expression domains are tightly linked, as separable regulatory elements for any given domain of Math1 expression were not found, suggesting that a common regulatory mechanism controls these apparently unrelated domains of expression. In addition, we demonstrate a role for autoregulation in controlling the activity of the Math1 enhancer, through an essential E-box consensus binding site.

Astrocyte Form and Function in the Developing Central Nervous System

Astrocytes have long been forgotten entities in our quest to understand brain function. Over the last few decades, there has been an exponential increase in our knowledge of central nervous system (CNS) function, and, consequently, astrocytes have emerged as key figures in CNS physiology and disease. Indeed, several pediatric neurologic disorders have recently been linked to astrocyte dysregulation, including leukodystrophies, autism spectrum disorders, and epilepsy. Given that pediatric disorders are rooted in developmental processes, the goal of this review is to catalog what we know about astrocyte development and function in the developing CNS. Moreover, we highlight current challenges and questions that remain in the field about astrocyte development. Our hope is that this review illuminates the potential of astrocytes and their associated developmental and physiological functions as potential therapeutic targets for the treatment of neurologic disorders.


George F. Cahill, Jr., then an associate professor of Medicine at Harvard Medical School and director of the Joslin Research Laboratory, was one of a very few clinical investigators who thought that the metabolism of starving humans should be reinvestigated in detail. In 1965, I was afforded a fellowship position in metabolism under the tutelage of Dr. Cahill, who in conjunction with his other academic appointments served on the professional staff of the Peter Bent Brigham Hospital. He was a creative and colorful medical director who had assembled a vibrant, cohesive research laboratory that was staffed by outstanding junior faculty, fellows, and proud, hard working, bright technicians who strove for exactness. The Peter Bent Brigham Hospital had a National Institutes of Health-supported clinical research center where patients could be housed and continuously observed during experimental protocols. A classical study by Cahill and colleagues was published in 1966 in The Journal of Clinical Investigation [ 4 ], which reported the hormone-fuel interrelationships during a 1-week fast (subjects consumed only water, salt, and vitamins during their starvation period) in six healthy subjects and two patients with type 2 diabetes mellitus. This article laid some of the groundwork for subsequent studies of prolonged starvation in obese humans.

When we began studying the energy requirements of adult humans and determining the organ or regional metabolism in these individuals, there were considerable gaps in our knowledge. It was probable that 1 g of urinary nitrogen could be equated to hepatic synthesis of about 3 g of glucose, that glucose synthesis occurred primarily from protein but not from fat, and that the brain used about 125 g of glucose daily to meet its energy requirements. In addition, the quantity of glucose stored as glycogen in the body was limited to approximately 1 day's supply. It was also known that only one-half of the body nitrogen (protein mass) could be mobilized during starvation, before death occurred. An average adult has about 1,000–1,200 g of nitrogen (mainly as muscle protein), but only 500–600 g can be mobilized before death occurs. This suggests that only 1,500–1,800 (500–600 × 3) g of glucose could be synthesized in the body during that period. If the brain continued to oxidize 100–145 g of glucose daily during starvation, survival would be limited to a minimum of 10 (1,500/145) and to a maximum of 18 (1,800/100) days. These calculations did not match the facts known at that time. First, obese humans consuming only water could usually live about 2 months. Second, to synthesize 100–145 g of glucose daily, the urinary excretion rate of nitrogen would have to be about 33 (100/3) to 48 (145/3) g the quantities of urinary nitrogen that were excreted during starvation were much less than these estimates.

We recognized the discrepancy between the requirement of the brain for glucose and the quantity of nitrogen excreted during starvation [ 2 ]. However, the quantity of nitrogen and the complete nature of the nitrogenous compounds excreted in the urine had not been clearly defined at that time. Furthermore, there was a verbal controversy regarding the ratio of urinary nitrogen and glucose production, and the sites of glucose production in the body during starvation had not been definitively established. Nonetheless, the quantity of glucose that can be totally oxidized to CO2 and water is considerably less than the 100–145 g/day required by the nervous system. Therefore, some fuel other than glucose must be providing the energy for the brain during starvation. When we began studying metabolic adaptations during starvation in humans, we did not know how long a person could fast and what fuels would be used by specific tissues. Once new insight began to accumulate, the energy requirements of all organs and the body as a whole had to be reevaluated.

Ubiquitinated protein degradation pathway

Ubiquitination is integral to the proteolytic system. Ubiquitin possesses 76 amino acid residues and is highly conserved from yeast to humans. It also possesses some non-proteolytic functions, including vesicle trafficking via ubiquitination of membrane proteins, protein kinase activation, DNA repair and chromatin dynamics through monoubiquitinated histone. A common mechanism involves ubiquitin or polyubiquitin chains recruiting ubiquitin receptors to perform biological functions [37].

Ubiquitin is involved in three degradation pathways (UPS, lysosome and autophagy). The triage of ubiquitinated proteins is probably based on their location, the ubiquitin chain length and the linkage types. The three degradation pathways may be interdependent on the ubiquitin pool in the cell [38]. Based on the lysine residues inside ubiquitin, seven homogeneous polymer chain linkages can be defined: K6, K11, K27, K29, K33, K48 and K63 [39].

The K48 chain is a classical sign of proteasomal degradation [39]. K63 is a common marker in the autophagy process [40]. However, recent studies revealed that the proteasome seems to accept almost all types of ubiquitin chain, including homogenous, heterogeneous, linear, head-to-tail, single and multi-branched chains and even those with mono- or multi-monoubiquitination [39, 41]. It is believed that ubiquitin polymer chains consist of at least four ubiquitin moieties [38]. Autophagy can also accept many types of ubiquitin chain [42].

It should be noted that K48 is still the common linkage targeting proteins to the proteasome. During proteasomal degradation, the length of the substrate proteins determines whether the process is mediated by mono- or polyubiquitination [43]. The existence of linkage multiplicity implies subtle alterations that contribute to the strength and/or conformation of the interaction between the proteasome and the substrates. Subtle alterations may control their “priority” to the proteasome, resulting in altered degradation rates that give rise to multiple biological functions [39].

The UBA domain of p62 can bind K48 and K63 (with a higher affinity for K63) [40, 44, 45]. UBA phosphorylation may enhance the affinity for K48 and K63 [46]. The longer ubiquitin chains show higher affinity for p62 [23]. K11 and K13 are thought to have non-proteolytic functions [47], and the other polyubiquitin chains have functions that remain unclear.

Determining the overall contribution of UPS and autophagy to ubiquitinated protein degradation is a topic of considerable interest. Studies with subjects ranging from Drosophila to mice suggest that the inactivation of autophagy by pharmacological or genetic inhibition causes the accumulation of ubiquitinated proteins in the brain [48, 49], skeletal muscle, cardiac muscle, pancreatic β-cells, podocytes and hepatocytes. However, Natura et al. obtained the opposite results [26]. In their study, they compared the turnover dynamics of endogenous ubiquitinated proteins by proteasome and autophagy by assessing the effects of their inhibitors. They found that pharmacological or genetic inhibition of autophagy could not increase the ubiquitinated protein level, although proteasome inhibition by epoximycin did. However, many proteins are degraded by both UPS and autophagy [2, 50]. Different cell lines may account for this discrepancy.

Materials and Methods

Fly Stocks

lbe 12C005 [31]. Df(lbl-lbe)B44, UAS-lbe, and ladybird early fragment K driving lacZ (referred to as lbe(K)-lacZ) (provided by C. Jagla) [32]. lbe(K)-EGFP [40]. elav-Gal4 (provided by A. DiAntonio) [41]. prospero-Gal4 (F. Matsuzaki, Kobe, Japan). cas Δ1 and cas Δ3 (provided by W. Odenwald) [42]. UAS-nls-myc-EGFP (referred to as UAS-nmEGFP) [11]. col 1 , col 3 [43] and UAS-col (provided by A. Vincent) [44]. hkb 5953 (referred to as hkb lacZ ) [45]. UAS-ap and ap md544 (referred to as ap Gal4 )[46]. ap rK568 (referred to as ap lacZ ) [47]. UAS-grn-HA (#F001916 provided by FlyORF). grh IM [48]. hb P1 , hb FB and Kr 1 , Kr CD [27], unpg 1912-r37 = unpg-lacZ (provided by C.Q. Doe) [23]. Antp 12 (provided by F. Hirth) [49]. ind-lacZ and en-lacZ (provided by H. Reichert). grn-lacZ, grn 7L12 , grn SPJ9 , UAS-grn (provided by J. Castelli-Gair Hombría). col- dAp-GFP was generated by inserting a genomic fragment from the col gene into the vector pEGFP.attB (provided by K. Basler and J. Bischof) and generating transgenes by PhiC31 transgenic integration (BestGene Inc, California, United States).

From Bloomington Drosophila Stock Center: Antp 25 (BL#3020). Df(2L)ED773 (removes both nub and Pdm2 BL#7416). mirr-lacZ (mirr B1-12 BL#30023). elav C155 = elav-Gal4 (BL#458). elav-Gal4 (BL#8765). hth 5E04 (BL#4221). Df(3R)Exel6158 (BL#7637 referred to as hth Df3R ). Mutants were maintained over GFP- or YFP-marked balancer chromosomes. As wild type, w 1118 or OregonR was used. Staging of embryos was performed according to Campos-Ortega and Hartenstein [50].

Exploratory Screen to Study Nplp1 Specification

The following transcription factor mutants were scored for changes in Nplp1 expression, without any apparent effects: escargot (esg), shuttle craft (stc), elbow/No ocelli (el/noc), rotund (rn), eagle (eg), kruppel homolog (kr h), knirps (kni), schnurri (shn), klumpfuss (klu), zfh2, dachshund (dac), defective proventriculus (dve), seven up (svp), vein (vn), beadex (bx), scribbler (sbb).


Primary antibodies were: Guinea pig a-Deadpan (1:1,000) (provided by J.B. Skeath). Rabbit a-ß-Gal (1:5,000 ICN-Cappel, Aurora, Ohio, US). Rabbit a-GFP (1:500 Molecular Probes, Eugene, OR, US). Guinea pig a-Col (1:1,000), guinea pig a-Dimm (1:1,000), chicken a-proNplp1 (1:1000), and rabbit a-proFMRFa (1:1,000). Rat a-Grh (1:1,000). Rabbit a-Cas (1:250) (provided by W. Odenwald). Rat mAb a-GsbN (1:10) (provided by R. Holmgren). Mouse a-Nubbin (referred to in the figure as Nub [Pdm] 1:20) (provided by Steve Cohen). Mouse mAb a-Dac dac2–3 (1:25), mAb a-Antp (1:10), mAb a-Pros MR1A (1:10), mAb a-Eya 10H6 (1:250) (Developmental Studies Hybridoma Bank, Iowa City, Iowa, US). Guinea pig anti-Odd (1:500) guinea pig anti-Runt (both provided by M. Ruiz and D. Kosman). Rat a-Msh (1:500) (provided by Z. Paroush) [51].

Confocal Imaging and Data Acquisition

Zeiss LSM 700 or Zeiss META 510 Confocal microscopes were used for fluorescent images confocal stacks were merged using LSM software or Adobe Photoshop. Statistic calculations were performed in Graphpad prism software (v4.03). To address statistical significance, Student's t test or nonparametric Mann-Whitney U test or Wilcoxon signed rank test, in the case of non-Gaussian distribution of variables, was used. Images and graphs were compiled in Adobe Illustrator.

Mash1 regulates neurogenesis in the ventral telencephalon

Previous studies have shown that mice mutant for the gene Mash1 display severe neuronal losses in the olfactory epithelium and ganglia of the autonomic nervous system, demonstrating a role for Mash1 in development of neuronal lineages in the peripheral nervous system. Here, we have begun to analyse Mash1 function in the central nervous system, focusing our studies on the ventral telencephalon where it is expressed at high levels during neurogenesis. Mash1 mutant mice present a severe loss of progenitors, particularly of neuronal precursors in the subventricular zone of the medial ganglionic eminence. Discrete neuronal populations of the basal ganglia and cerebral cortex are subsequently missing. An analysis of candidate effectors of Mash1 function revealed that the Notch ligands Dll1 and Dll3, and the target of Notch signaling Hes5, fail to be expressed in Mash1 mutant ventral telencephalon. In the lateral ganglionic eminence, loss of Notch signaling activity correlates with premature expression of a number of subventricular zone markers by ventricular zone cells. Therefore, Mash1 is an important regulator of neurogenesis in the ventral telencephalon, where it is required both to specify neuronal precursors and to control the timing of their production.

Learning Catalytics is an interactive, classroom tool that uses students' smartphones, tablets, or laptops to engage them in more sophisticated tasks and thinking. Now included with Mastering with eText, Learning Catalytics enables you to generate classroom discussion, guide your lecture, and promote peer-to-peer learning with real-time analytics. Instructors, you can:

  • Pose a variety of open-ended questions that help your students develop critical thinking skills.
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  • Use real-time data to adjust your instructional strategy and try other ways of engaging your students during class.
  • Manage student interactions by automatically grouping students for discussion, teamwork, and peer-to-peer learning.

Dee Unglaub Silverthorn studied biology as an undergraduate at Tulane University and received a Ph.D. in marine science from the University of South Carolina. Her research interest is epithelial transport, and recent work in her laboratory has focused on transport properties of the chick allantoic membrane. She began her teaching career in the Physiology Department at the Medical University of South Carolina but over the years has taught a wide range of students, from medical and college students to those still preparing for higher education. At the University of Texas-Austin she teaches physiology in both lecture and laboratory settings, and instructs graduate students on developing teaching skills in the life sciences. She has received numerous teaching awards and honors, including the 2009 Outstanding Undergraduate Science Teacher Award from the Society for College Science Teachers, the American Physiological Society’s Claude Bernard Distinguished Lecturer and Arthur C. Guyton Physiology Educator of the Year, UT System Regents’ Outstanding Teaching Award, and multiple awards from UT-Austin, including the Burnt Orange Apple Award. The first edition of her textbook won the 1998 Robert W. Hamilton Author Award for best textbook published in 1997—98 by a University of Texas faculty member. Dee recently completed six years as editor-in-chief of Advances in Physiology Education and she works with members of the International Union of Physiological Sciences to improve physiology education in developing countries. She is the incoming president (2012-13) of the Human Anatomy and Physiology Society, and an active member of the American Physiological Society, the Society for Comparative and Integrative Biology, the Association for Biology Laboratory Education, and the Society for College Science Teachers. Her free time is spent creating multimedia fiber art and enjoying the Texas hill country with her husband, Andy, and their dogs.

About the Illustrators
Dr. William C. Ober received his undergraduate degree from Washington and Lee University and his M.D. from the University of Virginia. While in medical school, he also studied in the Department of Art as Applied to Medicine at Johns Hopkins University. After graduation, Dr. Ober completed a residency in Family Practice and later was on the faculty at the University of Virginia in the Department of Family Medicine. He is currently an Affiliate Professor of Biology at Washington and Lee University and is part of the Core Faculty at Shoals Marine Laboratory, where he teaches Biological Illustration every summer.

Claire W. Garrison, R.N., B.A., practiced pediatric and obstetric nursing before turning to medical illustration as a full-time career. She returned to school at Mary Baldwin College where she received her degree with distinction in studio art. Following a five-year apprenticeship, she has worked as Dr. Ober’s partner in Medical & Scientific Illustration since 1986. She is on the Core Faculty at Shoals Marine Laboratory and co-teaches the Biological Illustration course.

As Medical and Scientific Illustration, some of this team’s titles include Human Anatomy (Benjamin Cummings), Integrated Principles of Zoology (McGraw-Hill), Biology (Raven/Losos, McGraw-Hill), Marine Biology (McGraw-Hill) and Galapagos Marine Life Series (Sugar Spring Press).

Watch the video: Δυναμώνω το νευρικό μου σύστημα. Τα πρώτα βήματα (December 2021).