Obesity and Type 2 Diabetes

1
Brain
Food
GI
Heart
Oxy
Controlling Energy (Controlling diabetes?)
Lac/ph
Glu
Triglyc
Muscle
John Doyle Caltech
FFA
Out
Glyc
Liver
Glycerol
Glyc
Fat
2
Brain
Energy
Food
GI
Heart
Oxy
Lac/ph
Glu
Triglyc
Muscle
FFA
Out
Glyc
Liver
Glycerol
Glyc
Fat
3
slow
dynamics
fast
Brain
high
Food
GI
Heart
Oxy
Lac/ph
Glu
priority
Triglyc
Muscle
FFA
Out
Glyc
low
Liver
Glycerol
Glyc
Fat
4
slow
dynamics
fast
Brain
high
Tight control of circulating metabolites
Heart/ lungs
Oxy
Glu
priority
Lac/ph
Muscle
FFA
Out
Glyc
low
Liver
Insulin sensitivity?
Fat
5
fast
high
Oxy
Circulating metabolites
Lac/ph
Glu
Triglyc
FFA
Glycerol
6
Brain
GI
Heart
Organs
Muscle
Liver
Glyc
Glyc
Fat
7
Storage
Glyc
Glyc
Fat
8
Feeding
Brain
slow
Food
GI
Heart
GIP GLP-x
Glu
Triglyc
Muscle
Insulin
Glyc
Liver
Glyc
Adipokines Leptin Adiponectin resistin
Fat
9
Brain
slow
high
Heart
Fasting
Glu
priority
Insulin Glucagon
Muscle
FFA
Glyc
Liver
low
Glycerol
Glyc
Fat
10
Brain
fast
Active
high
Heart
Oxy
Glu
Muscle
FFA
Out
Glyc
Liver
low
Glycerol
Glyc
Fat
11
Brain
fast
Intense
high
Heart
Oxy
Lac/Ph
Glu
Muscle
Out
Glyc
Liver
low
Glyc
12
slow
dynamics
fast
Brain
high
Heart
Intense
Glu
priority
Muscle
Glyc
low
Liver
Glyc
Fat
13
slow
dynamics
fast
Brain
high
Heart
Fasting
Glu
priority
Muscle
Glyc
low
Liver
Glyc
Fat
14
slow
dynamics
fast
Brain
high
Heart
Feeding
Glu
priority
Muscle
Glyc
low
Liver
Glyc
Fat
15
slow
dynamics
fast
Brain
high
Active
Heart/ lungs
Glu
priority
Muscle
FFA
Out
Glyc
low
Liver
Fat
16
slow
dynamics
fast
Brain
high
Active
Heart/ lungs
Glu
priority
Muscle
FFA
Out
Glyc
low
Liver
days! (hours?) (min?)
Fat
17
Brain
slow
Food
GI
Heart
Active Feeding
Active
Glu
Triglyc
Muscle
Insulin
Out
Glyc
Liver
Glyc
Fat
18
Type 2
Brain
?Active
Glu
Muscle
Glyc
Liver
Fat
Glyc
19
Type 2
Brain
Food
GI
Heart
?GIP ?GLP-1
DJB
Glu
Triglyc
Muscle
Glyc
Liver
Fat
Glyc
Adipokines ?unchanged
20
dynamics
fast
Brain
high
HR
Tight control
Heart/ lungs
Oxy
Glu
priority
Lac/ph
Muscle
FFA
Watts
Glyc
Liver
Fat
21
500
not
400
watts
300
Everyone has an individual performance envelope
achievable
200
Simple
100
0
sec
min
hour
days
year
Log(time)
22
Humans have an amazing performance range
23
The rest of these will focus on under an hour and
will be linear (not log) in time.
500
400
Hard
watts
300
Hard
Easy exercise
Hard
200
Easy warmup /ending
100
0
30 min
1 hour
Linear time
24
Complexity in the models will arise around the
edges of the performance envelope due to a
variety of mechanisms.
500
400
Hard exercise
Complex
watts
300
Hard exercise
Complex
Hard exercise
200
Complex
Simple
Complex
Easy warmup and ending
100
Complex
0
30 min
1 hour
Linear time
25
Complexity here involves saturations as the
intensity approaches hard limits.
500
400
Hard exercise
Complex
watts
300
Hard exercise
Complex
Hard exercise
200
Complex
100
0
30 min
1 hour
Linear time
26
Complexity here arises because of warmup
dynamics, and at low intensities, the presence of
unmeasured (internal) loads.
500
400
watts
300
200
Complex
Easy warmup and ending
100
Complex
0
30 min
1 hour
Linear time
27
Suppose we have one workout like this with 4
periods, each of maybe 20-30 minutes. (It will
actually be difficult to get all of the desired
data at one time.)
3. Hard exercise
level
2. Easy exercise
4. Easy ending
1. Easy warmup
time
28
This part by itself will have the simplest model,
which can be linear and low (even first) order.
If the changes in watts are sufficiently slow, a
static model may be ok.
2. Easy exercise
29
These together will be more complex because of
the warmup process involving vasodilation and
blood pressure control. More dynamic states, but
not more nonlinearity? At least one exercise
should be largely aerobic, with some data at pure
rest, easy warmup, fluctuations within the
aerobic range, and an easy warmdown, and then
some time at rest.
2. Easy exercise
1. Easy warmup
4. Easy ending
30
This will need nonlinearities because of
saturations, which will be different depending on
time and intensity. Saturations occur as effort
increases in aerobic capacity, acid buffering,
and ultimately anaerobic capacity.
3. Hard exercise
Saturations also occur on long time scales due to
substrate depletion, first by anaerobic glycogen
depletion, then aerobic processes, and liver
energy depletion.
31
Will parts 2,3, and 4 together need more states
or complex nonlinearities than part 3 needs by
itself? One or more exercises should push into
the higher intensity regime.
3. Hard exercise
2. Easy exercise
4. Easy ending
The ending will show higher HR than in part 2 at
the same watt levels due to fatigue.
32
Conjecture it will be possible to model both of
these in one linear model but with more states
than stage 2 would have by itself, because of
fatigue
2. Easy exercise
4. Easy ending
Note the slowest p states will be roughly
constant during each of these but larger during
period 4 due to fatigue
33
Summary (conjecture)
More nonlinear
3. Hard exercise
2. Easy exercise
2. Easy exercise
3. Hard exercise
2. Easy exercise
4. Easy ending
2. Easy exercise
More states
3. Hard exercise
4. Easy ending
1. Easy warmup
2. Easy exercise
4. Easy ending
1. Easy warmup
2. Easy exercise
3. Hard exercise
4. Easy ending
34
If this is roughly correct, then the right single
exercise (or perhaps several exercises) can
explain how various mechanisms come in We may
ultimately be able to design a single exercise
for all regimes, but for now well try to get a
few that do.
anaerobic
More nonlinear
Summary (conjecture)
3. Hard exercise
2. Easy exercise
2. Easy exercise
fatigue
3. Hard exercise
2. Easy exercise
4. Easy ending
2. Easy exercise
3. Hard exercise
BP control
4. Easy ending
1. Easy warmup
2. Easy exercise
4. Easy ending
1. Easy warmup
2. Easy exercise
3. Hard exercise
4. Easy ending
More states
35
The aim is to get data that explores the whole
regime, and also has changes of very different
frequency content.
500
400
Hard exercise
Complex
watts
300
Hard exercise
Complex
Hard exercise
200
Complex
Simple
Complex
Easy warmup and ending
100
Complex
0
30 min
1 hour
Linear time
36
Review Article The critical power and related
whole-body bioenergetic models R. Hugh Morton1 
      
European Journal of Applied Physiology 2005
37
Glucose
Blood
Oxygen
mitochondria
muscle
ATP
Easy
Aerobic
38
buffer
500
400
300
200
100
mitochondria
0
0
5
10
15
Easy
Aerobic
39
Glucose
Blood
Oxygen
Liver
muscle
body
muscle
Anaerobic
Hard
Aerobic
40
Glucose
Blood
Oxygen
Liver
Acid buffer Cori cycle
body
Hard
41
Acid buffer Cori cycle
Anaerobic muscle
aerobic
Liver
42
Glucose
Blood
Oxygen
Liver
muscle
body
Anaerobic
Hard
Aerobic
43
buffer
500
400
300
liver
200
100
mitochondria
0
0
5
10
15
Anaerobic
Hard
Aerobic
44
Glucose
Oxygen
Liver
muscle
Anaerobic
Severe
Aerobic
45
Glucose
Oxygen
Liver
muscle
Empty
Anaerobic
Failure
Aerobic
46
500
buffer
400
watts
300
200
100
0
0
5
10
15
20
25
30
Time (min)
liver
mitochondria
Anaerobic
Severe
Aerobic
47
buffer
500
400
300
liver
200
100
mitochondria
0
0
5
10
15
Lactic acid buffer
Finite energy buffer
48
Review Article The critical power and related
whole-body bioenergetic models R. Hugh Morton1 
      
European Journal of Applied Physiology 2005
49
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50
buffer
Anaero glycogen
300
watts
250
200
150
Aero glycogen
100
50
0
0
1
2
3
10
10
10
10
Time (min)
Anaerobic
mitochondria
Aerobic
51
300
Anaero glycogen
watts
250
200
150
Aero glycogen
100
50
0
0
1
2
3
10
10
10
10
Time (min)
mitochondria
Glycogen (pyruvate)
Anaerobic
fat
Aerobic
52
Running world records
buffer
12
speed
Aerobic glycogen
36.0
10
28.8
8
21.6
6
14.4
4
2
0
1
2
3
4
5
10
10
10
10
10
day
min
hr
10 min
53
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