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Burrascano's Guidelines
and
Immune Response Modeling
Mathematical Immune Response Models
In some infectious diseases other than Lyme it is an established procedure to mathematically model the immune response, in order to
-
investigate the processes involved and
-
more effectively monitor and adjust
therapy
(see Tables of Contents in [1,
2]).
General Features of Infections and Models
In particular, researchers have been able to mathematically model and often verify in vivo or in vitro the following possible states of the infection [3, 4, 5, 6, 7]
-
an asymptotic
decrease of antigen quantity,
-
approach of its
quantity towards constant value (example: chronic inflammation of the sinus-maxillary floor, peristent lyme arthritis).
-
periodic course
of the illness,
-
unlimited growth
of the antigen quantity.
There are obvious similarities to Lyme.
Model Sophistication in Lyme Disease
Applying established procedures used
in constructing models of infections, we modeled the immune response to
Borrelia burgdorferi (Bb) or Bb fragments with one
or a set of
two non-linear
differential equations.
The model
represents the observed recurrence of Lyme (for details see summary [10]
or draft report [11]).
Input Data
As long as our laboratory diagnostic
techniques sometimes produce results that seem to be inconsistent
with our clinical findings, the information the ill person is able to provide
about the status of his/her disease needs to be discussed.
-
J.J. Burrascano recommended his patients
to "keep a carefully detailed daily diary of their symptoms to help judge
the effects of treatment, the presence of the classic four week cycle,
and treatment endpoint" [8].
-
We took
-
J.J. Burrascano's Symptom
Checklist and
-
J.D. Bleiweiss' essay "When
to suspect Lyme" [9]
as starting points for our list. To
visualize possible cyclical symptoms occurrence, we
-
entered the data into a spreadsheet,
where the symptoms are arranged horizontally and time on the vertical axis.
Often, cycles become apparent already in this representation.
-
statistically
analyzed the data for periodicities (example).
Immune Response Modeling in Lyme - A Path to Improved Treatment
J.J. Burrascano's therapy
guidelines (see "Course During Therapy" in Chapter "Lyme
Disease Treatment Guidelines") are based on his experience that
-
the described immune response model
approach
-
is applicable to Lyme and
-
increases the chances of recovery compared
to a therapy of fixed duration.
-
the actual adaptation and verification
of the model for Lyme disease can be done with the data from his patients'
files.
References
1. Models of immune
sytems - The use of differential equations,
literature
survey, April 2000.
2. Mathematical immune
response models, literature
survey, April 2000.
3. Dibrov BF,
Livshits MA, Vol'kenshtein MV,
Mathematical
model of the immune response, 1976.
4. Dibrov BF,
Livshits MA, Vol'kenshtein MV,
Mathematical
model of the immune response. IV. Threshold character of the infectious
process, 1978.
5. McKenzie FE,
Bossert WH, The
dynamics of Plasmodium falciparum blood-stage infection, 1997.
6. Muraille E,
Thieffry D, Leo O, Kaufman M,
Toxicity
and neuroendocrine regulation of the immune response: a model analysis,
1996.
7. De Boer RJ,
Perelson AS, Kevrekidis IG, Immune
network behavior--I. From stationary states to limit cycle oscillations,
1993.
8. Burrascano
JJ, Managing Lyme
disease: diagnostic hints and treatment guidelines for Lyme borreliosis,
in: Conn's Current Therapy - Latest Approved Methods of Treatment for the
Practicing Physician, pp.140-143, Harcourt Brace & Company, 1997.
9. Bleiweiss JD,
When to suspect Lyme disease, early
1990's.
10. Gruber J,
Evaluation
of the long-term inflammation in neuroborreliosis, 1999.
11. Gruber J,
Compartment
Model Displaying Symptom Cycles, 1999.
Version: August 18, 2004.
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