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Dear Jeff,

I will try to answer your questions one by one.

> To answer Kevin's question, it wasn't me doing the
> experiments, but someone using our center.  I'm pretty sure 
> controls were not done in order to establish the 
> Stokes-Einstein relation using different viscosity solutions 
> of the probe (YFP in this case), because the experiments only 
> needed to show relative, not absolute, differences in diffusion rates.

Actually, checking whether you can find the Stokes-Einstein relationship for
a viscosity series is a controll for the ability to correctly measure
*relative* diffusion coefficients. If a linear relation between D and
1/viscosity is not found, one is not able to correctly measure relative
diffusion coefficients. In my opinion this is the primary experiment one
should start with before applying a FRAP method to other samples. In
addition, to see your method is able to correctly measure absolute diffusion
coefficients, a comparison should be made with independent diffusion
measurements.


> So my question was geared towards those applications where it
> was not necessary to know accurately the diffusion rates, but 
> just be able to show differences, and know in which direction 
> the differences occurred, simply by looking at the half-life 
> of the recovery phase.

That would be sufficient for qualitative experiments, indeed.

 
> Thanks for pointing out that a change in cell morphology, one
> which changes the travel length required for diffusing 
> molecules to repopulate the bleached region, could cause a 
> change in the recovery half-life, while the diffusion rate 
> remained unchanged.  I think that's an important point.  I 
> had asked for an explanation for a change in recovery 
> half-life that was not indicative of a change in diffusion 
> rate, and I got one.

Don't forget about the amount of photobleaching which determines the shape
of the recovery curve as well (see previous postings and below)!

 
> However, I still have two questions.
> 
> 1) I am still unclear as to how a change in the amount of 
> photobleaching, NOT CAUSED BY A DIFFERENCE IN DIFFUSION RATE, 
> could affect the recovery half-life.  The difference in 
> photobleaching could be caused by a difference in chemical 
> environment that does not change viscosity, as you put forth. 
> In such a case where the difference in photobleaching amount 
> is not accompanied by a difference in photobleaching volume, 
> shouldn't the recovery half-life be the same? (as long as the 
> curve is corrected for any significant differences in total 
> fluorescence inside + outside bleached
> region)

I don't quite understand the confusion. Since the more qualitative
explanation in the previous posting didn't help, perhaps it is a little
easier to understand if I put it in a more formalistic mathematical way:

To calculate the recovery curve, one has to solve Fick's second law of
diffusion, which is a partial differential equation. To obtain a specific
solution to a differential equation, one has to provide an initial condition
for which the differential equation has to be solved. In case of FRAP, the
initial condition for the solution of the diffusion equation is the
situation right after photobleaching. The situation after photobleaching is
in fact the particular geometry which has been photobleached to a certain
extent. So in FRAP, the initial condition is basically dependent on two
parameters: the bleach geometry and the amount of photobleaching. Now, if
the initial condition is a function of the amount of photobleaching, the
final solution to the diffusion equation (i.e. the recovery curve) will be
as well!

To see an example, have a look at one of the fundamental papers on FRAP:

Axelrod, D., D.E. Koppel, J. Schlessinger, J. Elson, and W.W. Webb.1976.
Mobility measurement by analysis of fluorescence photobleaching recovery
kinetics. Biophys. J. 16:1055-1069.

Eq. 12 is the recovery curve after bleaching of a Gaussian spot. In this
equation you will indeed see a parameter 'K', which is a measure for the
amount of photobleaching. So there you can actually see explicitly the
dependency of the recovery curve on the amount of photobleaching.

In the same article, also have a look at Fig. 3: there the dependency of the
recovery half-time on the amount of photobleaching is actually plotted!


> 2) In such a case where a change in the diffusion rate 
> changes not only the photobleached amount but the size of the 
> photobleached volume, by virtue of non-instantaneous 
> bleaching, what exactly would the effect be on the recovery 
> half-life?  I'm assuming that the answer to the previous 
> question is "yes", so that I am interested more in the effect 
> induced by the change in effective photobleached volume. 
> Would it be true that the half-life actually increases when 
> the diffusion rate has shortened?

If the condition of instantaneous photobleaching is not met, by the
beginning of the recovery phase photobleached molecules will already have
moved outside the bleached area. This means that the photobleached area will
actally be larger than expected from the bleach geometry alone. As a
consequence, because the recovery time depends on the square (!) of the
photobleached area, the recovery half-time will be shifted to a larger value
and the measured diffusion coefficient will be an underestimate of the real
value.

It is really easy to test this for yourself. Just perform FRAP experiments
on the same solution with gradually increasing photobleaching times. You
will see a decrease in the measured diffusion coefficient if the bleaching
time increases.

I hope this helps.

Best regards,

Kevin

 
> > -----Original Message-----
> > From: Kevin Braeckmans [mailto:[log in to unmask]]
> > Sent: Thursday, November 25, 2004 6:20 AM
> > To: [log in to unmask]
> > Subject: Re: FRAP experiments
> >
> >
> > Search the CONFOCAL archive at 
> > http://listserv.acsu.buffalo.edu/cgi-bin/wa?S1=3Dconfocal
> >
> > Dear Jeff,
> >
> > First of all, it is great that you get consistent results using the 
> > empirical FRAP method; in the end it is the experiment alone which 
> > gives = the final proof. To be clear, I didn't mean to say 
> it doesn't 
> > work, it is = just that, according to my understanding, 
> there may be 
> > some pitfalls = associated with the method which might be hard to 
> > avoid or even notice, certainly = for someone relatively new to
> > quantitative FRAP experiments.
> >
> > I will try to explain my reservations about the method, which are 
> > purely from a theoretical point of view. But I may very well be 
> > mistaking, so please correct me if I am wrong; it is always 
> > advantageous to gain new insights.
> >
> > In a FRAP experiment, the fluorescence recovery happens after = 
> > photobleaching because of diffusion. In general, the shape of the 
> > recovery curve will depend on 1) the amount of 
> photobleaching, 2) the 
> > bleach geometry (shape =
> > +
> > size), 3) sample space (e.g. 2D or 3D) and 4) the diffusion speed. 
> > Therefore, to obtain the diffusion coefficient from the recovery 
> > curve, = one has to take the amount of photobleaching, the bleach 
> > geometry and the = sample space carefully into account. And this is 
> > exactly what is done by the various FRAP models which are 
> based on a 
> > solution of Fick's second law = for those particular boundary 
> > conditions.
> >
> > The empirical method, at the other hand, is based on the assumption 
> > that = if one keeps all boundary conditions the same for each 
> > experiment, a change = in the recovery curve can only be due to a 
> > change in diffusion coefficient. Therefore, by comparing 
> the recovery 
> > curves from two experiments one can obtain a relative change in 
> > diffusion coefficient. As already said, this sounds like a very
> > reasonable approach, and very easy to carry out as = well.
> >
> > In actual practice, howver, it seems to me that it will be very = 
> > difficult (if possible at all) to obtain the same boundary 
> conditions 
> > in two = different samples. My major concern is the 
> condition of the 
> > amount of = photobleaching which has to be exactly the 
> same, because 
> > for the same laser intensity, = the amount of photobleaching can be 
> > very different for a low and a high viscosity sample (see my
> > previous e-mail). In addition, if the chemical environment is
> > different for both samples, the photobleaching rate and =
> > hence the amount of photobleaching can be very different as
> > well. According to = the reasoning above, if the amount of
> > photobleaching is different, the two recovery curves cannot
> > be compared directly in terms of a change in diffusion
> > coefficient alone.
> >
> > In addition, also the following two issues are critical to obtain = 
> > correct values for the diffusion coefficient.
> >
> > 1. For the same photobleaching time, more recovery will 
> have happened 
> > = for a fast diffusing sample compared to a more slowly 
> diffusing one. 
> > As a consequence, the bleached geometry in the fast sample will 
> > generally be expanded compared to the slow sample. Again, if both 
> > bleach geometries = are not exactly the same, the recovery curves 
> > cannot be compared any more. Therefore it will be of critical 
> > importance that the condition of an instantaneous bleach phase is 
> > respected. (This is the same for most of = the 'physical' 
> FRAP models, 
> > though.)
> >
> > 2. The sample space in which diffusion takes place should 
> be the same 
> > = for both samples. While this is not a problem when doing 
> experiments 
> > in 3D samples such as solutions etc., one can imagine that the 3D 
> > structure of = a biological sample can be very different 
> for different 
> > locations. In = cells for example, the nuclear area is thicker 
> > compared to the cytoplasmic = area towards the edges. So one can 
> > imagine that the axial diffusion = contribution to the 
> recovery curve 
> > will be different for both regions. Again, this is also an issue
> > for some of the physical FRAP models.
> >
> > So in conclusion, although it should be possible for the 
> empirical = 
> > method to work, I think it may be challenging to get correct 
> > measurements. But you seem to get good results with it, 
> which is great 
> > of course. Can I ask, = did you ever try to apply the method to a 
> > viscosity series of the same probe = and check whether you 
> can obtain 
> > the Stokes-Einstein relation (D propotional = to the reciprocal 
> > viscosity)?
> >
> > Best regards,
> >
> > Kevin
> >
> > -----Oorspronkelijk bericht-----
> > Van: Confocal Microscopy List 
> [mailto:[log in to unmask]] = 
> > Namens Reece, Jeff
> > (NIH/NIEHS)
> > Verzonden: woensdag 24 november 2004 16:29
> > Aan: [log in to unmask]
> > Onderwerp: Re: FRAP experiments
> >
> >
> > Search the CONFOCAL archive at 
> > http://listserv.acsu.buffalo.edu/cgi-bin/wa?S1=3Dconfocal
> >
> > Kevin,
> > Could you or another FRAPper elaborate on one of your points?
> >  Re: the "empirical" methods that you don't recommend, you 
> explain the 
> > = variability in photobleaching rates by what seems a reasonable 
> > assumption: variability = in viscosity, causing variability in 
> > diffusion rates.  In other words, it = seems that such a 
> measurement 
> > of diffusion rate is therefore reporting what it = is supposed to 
> > report, and the variability can be summarized as unavoidable 
> > variability in cell morphology.  Let me know what I'm missing here.
> >
> > Even if the variability in photobleaching is not caused by 
> variability 
> > = in diffusion rates, what else besides a changing diffusion rate 
> > could = explain a change in recovery half-life?  Even if 
> there is more 
> > variability in the empirical method (for whatever reason) than with 
> > methods offering near-instantaneous photobleaching, you should still
> > be able to overcome = the experiment-to-experiment
> > variability by ratioing to the same control in = each
> > experiment, and increasing the # samples.
> >
> > People here have gotten consistent results when FRAPping with the = 
> > empirical method, and of course I would like to know if we 
> > misinterpret = significant differences as indicating 
> varying diffusion 
> > rates.
> >
> > CHeers,
> > Jeff M. Reece
> > Biomedical Engineer
> > Confocal Microscopy Center
> > National Institute of Environmental Health Sciences (NIEHS) 111 
> > Alexander Drive, Bldg, 101, Rm. F219 P.O. Box 12233, MD F2-02
> > Research Triangle Park, NC  27709
> > (919) 541-0311
> > [log in to unmask]
> >
> >
> > > -----Original Message-----
> > > From: Kevin Braeckmans [mailto:[log in to unmask]]
> > > Sent: Wednesday, November 24, 2004 4:09 AM
> > > To: [log in to unmask]
> > > Subject: Re: FRAP experiments
> > >
> > >
> > > Search the CONFOCAL archive at=20 
> > > http://listserv.acsu.buffalo.edu/cgi-bin/wa?S1=3D3Dconfocal
> > >
> > > Dear Jammi,
> > >
> > > Calculating a diffusion coefficient from an FRAP experiment
> > is usually
> > > =
> >
> > > =3D based on the fitting of a particular FRAP model to the =
> > experimental=20
> > > =3D fluorescence recovery curve. Therefore, to obtain a valid =
> > diffusion=20
> > > coefficient, it =3D is of utmost importance that your
> > experiment is=20
> > > carried out according to the theory of the FRAP model you
> > want to use.
> > >
> > > Apart from a few exceptions, most FRAP models indeed assume
> > an =3D=20
> > > instantaneous photobleaching phase, which in fact is the
> > assumption of
> > > =
> >
> > > having no =3D recovery while photobleaching. Hence, the the time 
> > > for=20 photobleaching should be =3D very short (< 5%) compared to 
> > > your=20 experiment's characteristic recovery time. =3D In actual 
> > > practice this =
> >
> > > means that in most cases you can only use one =3D bleaching 
> > > iteration=20 (although it depends on many parameters:
> > scanning speed,
> > > =3D bleach=20 geometry, diffusion speed). For longer 
> photobleaching 
> > > times you will get =3D the 'corona' effect you mentioned,
> > leading in
> > > fact to a decreased (not
> > > increased) diffusion coefficient.
> > >
> > > As long as you respect this simple but important rule, the actual 
> > > =3D=20 percentage of photobleaching doesn't matter, at 
> least if you 
> > > are using =
> >
> > > a good FRAP model. With 'good' I mean a FRAP model which
> > takes the=20
> > > amount of photobleaching explicitly into account. For such
> > a FRAP=20
> > > model you can include this 'photobleaching parameter' as 
> a free=20 
> > > fitting variable to =3D obtain its value for each 
> experiment from a 
> > > fitting to the data.
> > >
> > > For completeness sake I should mention that there are FRAP
> > models=20
> > > which =3D do not require an instantaneous photobleaching
> > phase (see =
> > list=20
> > > below). One =3D is based on Fourier transforms, the other on a=20 
> > > statistical analysis. The Fourier method is very neat in theory, 
> > > but=20 doesn't seem to work very =3D well in actual
> > practice based on
> > > our own =
> >
> > > experience because it is very noise sensitive. Does anyone
> > of the=20
> > > Confocal List have a different experience =3D with this?
> > >
> > > Finally, there are also empirical FRAP methods which are based on 
> > > the=20 =3D idea that if one does exactly the same in each
> > sample (same
> > > bleach =
> >
> > > intensity, bleach time and bleach
> > > geometry) one can get a relative diffusion coefficient by
> > comparing=20
> > > the recovery-half-times. While this sounds a reasonable 
> assumption 
> > > in=20 theory, I wouldn't recommend it because in =3D actual
> > practice
> > > you =
> > will=20
> > > not get the same photobleaching result in different
> > samples, as you=20
> > > have observed for yourself in your own experiments. The =3D main 
> > > reason for this is that the photobleaching process is 
> based on =3D 
> > > photochemical reactions in which many different molecules
> > play a role.
> > > So for example, =3D in a high viscosity sample you will get less 
> > > photobleaching compared to a similar low viscosity sample
> > because in
> > > the latter the molecules are diffusing more rapidly, hence
> > increasing
> > > the number of photobleaching reactions per second, hence 
> leading to 
> > > more photobleaching. And things become even more complicated when 
> > > doing measurements in different =3D regions of a cell where the 
> > > chemical environment can differ as well.
> > >
> > > So as you can see it all comes down to which FRAP model you
> > will be =
> > =3D=20
> > > using for calculating the diffusion coefficient. In case you have 
> > > not=20 decided =3D yet which model to use, below is a (non
> > exhautive)
> > > list of =
> >
> > > possible FRAP models/methods.
> > >
> > > Hopefully this is of help to you.
> > >
> > > Best regards,
> > >
> > > Kevin Braeckmans, Ph.D.
> > > Lab. General Biochemistry and Physical Pharmacy
> > > Ghent University
> > > Belgium
> > >
> > >
> > > Here's the list.
> > >
> > > 1. Axelrod, D., D.E. Koppel, J. Schlessinger, J. Elson, and
> > W.W. Webb.
> > > =
> >
> > > =3D 1976. Mobility measurement by analysis of fluorescence=20 
> > > photobleaching recovery kinetics. Biophys. J. 16:1055-1069.
> > >
> > > This fundamental article covers 2D diffusion and 1D flow for 
> > > Gaussian=20 =3D and uniform spot photobleaching. A more practical 
> > > expression for=20 uniform =3D spot photobleaching has been
> > derived by:
> > >
> > > 2. Soumpasis, D.M. 1983. Theoretical analysis of
> > fluorescence =3D=20
> > > photobleaching recovery experiments. Biophys. J. 41:95-97.
> > >
> > > FRAP in 2D with the uniform spot method has been examined
> > for 2 =3D=20
> > > diffusing components as well:
> > >
> > > 3. Gordon, G.W., B. Chazotte, X.F. Wang, and B. Herman.
> > 1995. Analysis
> > > =
> >
> > > =3D of simulated and experimental fluorescence recovery after=20 
> > > photobleaching. =3D Data for two diffusing components.
> > Biophys. J.=20
> > > 68:766-778.
> > >
> > > A paper discribing FRAP for a Gaussian spot in case of
> > second order=20
> > > photobleaching kinetics:
> > >
> > > 4. Bjarneson, D. W., and N. O. Petersen. 1991. Effects of
> > second order
> > > =
> >
> > > photobleaching on recovered diffusion parameters from
> > fluorescence=20
> > > photobleaching recovery. Biophys. J. 60:1128-1131.
> > >
> > > A 3D extension of the Gaussian spot has been proposed by:
> > >
> > > 5. Blonk, J.C.G., A. Don, H. Van Aalst, and J.J.
> > Birmingham. 1993.=20
> > > Fluorescence photobleaching recovery in the confocal
> > scanning light=20
> > > microscope. J. Microsc. 169:363-374.
> > >
> > > And a similar 3D extension of the uniform spot was recently
> > derived by
> > > =
> >
> > > =3D us. The model is also applicable to bleaching disk-shaped =
> > geometries=20
> > > on =3D confocal scanning microscopes:
> > >
> > > 6. Braeckmans, K., L. Peeters, N. N. Sanders, S. C. De Smedt, and 
> > > J.=20 Demeester. 2003. Three-dimensional fluorescence recovery 
> > > after=20 photobleaching with the confocal microscope. Biophys. J. 
> > > 85:2240-2252.
> > >
> > > A numerical approach for the 2D uniform spot (or disk) has
> > been =3D=20
> > > presented
> > > by:
> > >
> > > 7. Lopez, A., L. Dupou, A. Altibelli, J. Trotard, and J.
> > Tocanne.=20
> > > 1988. Fluorescence recovery after photobleaching
> > > (FRAP) experiments under conditions of uniform disk
> > illumination.=20
> > > Biophys. J. 53:963-970.
> > >
> > > A numerical approach for 2D FRAP in a diffraction limited
> > line segment
> > > =
> >
> > > =3D was developed by:
> > >
> > > 8. Wedekind, P., U. Kubitscheck, O. Heinrich, and R.
> > Peters. 1996.=20
> > > Line-Scanning microphotolysis for diffraction-limited 
> measurements 
> > > of=20 lateral diffusion. Biophys. J. 71:1621-1632.
> > >
> > > and later in 3D as well:
> > >
> > > 9. Kubitscheck, U., P. Wedekind, and R. Peters. 1998.=20 
> > > Three-dimensional diffusion measurements by scanning 
> > > microphotolysis.=20 J. Microsc. =3D 192:126-138.
> > >
> > > A statistical evaluation of 2D FRAP for arbitrary radially 
> > > symmetric=20 bleaching geomteries has been presented as 
> well. This 
> > > method has the=20 advantage of being independent of the bleaching 
> > > kinetics and possible=20 recovery during bleaching. A
> > disadvantage is
> > > that it does not allow to =
> >
> > > calculate the immobile fraction independently.
> > >
> > > 10. Kubitscheck, U., P. Wedekind, and R. Peters. 1994. Lateral=20 
> > > diffusion measurements at high spatial resolution by scanning=20 
> > > microphotolysis in a confocal microscope. Biophys. J. 67:948-956.
> > >
> > > A method for 2D FRAP having essentially the same 
> advantages and=20 
> > > disadvantages, relies on a calculation involving Fourier
> > transforms of
> > > =
> >
> > > =3D the recovery images. An additional advantage is that
> > the bleaching
> > > =
> >
> > > geometry =3D is completely arbitrary. The following two articles =
> > explain=20
> > > how the =3D technique
> > > works:
> > >
> > > 11. Tsay, T., and K.A. Jacobson. 1991. Spatial Fourier
> > analysis of=20
> > > video photobleaching measurements, principles and 
> optimization.=20 
> > > Biophys. J. 60:360-368.
> > >
> > > which should be read in combination with
> > >
> > > 12. Berk, D.A., F. Yuan, M. Leunig, and R. K. Jain. 1993.
> > Fluorescence
> > > =
> >
> > > photobleaching with spatial Fourier analysis: measurement
> > of diffusion
> > > =
> >
> > > =3D in light-scattering media. Biophys. J. 65:2428-2436.
> > >
> > > A method for the analysis of a distribution of diffusion 
> > > coefficients=20 =3D (in stead of just 1 or 2) has been 
> described by:
> > >
> > > 13. Periasamy, N., and A. S. Verkman. 1998. Analysis of
> > fluorophore=20
> > > diffusion by continuous distributions of diffusion coefficients: 
> > > =3D=20 Application to photobleaching measurements of 
> multicomponent 
> > > and=20 anomalous =3D diffusion. Biophys. J. 75:557-567.
> > >
> > > A method for measuring relative diffusion coefficients by FRAP:
> > >
> > > 14. Kao, H. P., J. R. Abney, and A. S. Verkman. 1993. 
> Determinants 
> > > of=20 =3D the translational mobility of a small solute in cell 
> > > cytoplasm. J. =
> >
> > > Cell =3D Biol. 120:175-184.
> > >
> > > and later articles by the same authors. For a review of their 
> > > methods=20 =3D
> > > see:
> > > Verkman, A. S. 2003. Diffusion in cells measured by flourescence 
> > > =3D=20 recovery after photobleaching. In Biophotonics, Part
> > A: Methods
> > > in=20 Enzymology, =3D Volume 360. G. Marriott and I.
> > Parker, editors.
> > > =
> > Academic=20
> > > Press, New York, pp.635-648.
> > >
> > > 1D FRAP in a limited volume based on Fourier transforms was
> > derived=20
> > > by:
> > >
> > > 15. Elowitz,M.B.; Surette,M.G.; Wolf,P.E.; Stock,J.B.;
> > Leibler,S.=20
> > > 1999. Protein mobility in the cytoplasm of Escherichia 
> coli. J.=20 
> > > Bacteriology. 181:197-203.
> > >
> > > A FRAP model for 1D diffusion including association and
> > dissociation:
> > >
> > > 16. Carrero, G., D. McDonald , E. Crawford, G. de Vries,
> > and M. J. =3D
> > > =
> >
> > > Hendzel. 2003. Using FRAP and mathematical modeling to determine 
> > > the=20 in vivo =3D kinetics of nuclear proteins. Methods 29:14-28.
> > >
> > > A paper describing a 'Fringe Pattern Photobleaching and Recovery' 
> > > =3D=20 method, as well as a FRAP method relying on a uniformly 
> > > bleached long=20 line segment:
> > >
> > > 17. Cheng, Y., R. K. Prud'homme, and J. L. Thomas. 2002. 
> Diffusion 
> > > of=20 mesoscopic probes in aqueous polymer solutions 
> measured by=20 
> > > fluorescence recovery after photobleaching. Macromolecules=20 
> > > 35:8111-8121.
> > >
> > > An other paper describing FRAP in case of a long line segment:
> > >
> > > 18. Dietrich, C., R. Merkel, and R. Tampe. 1997. Diffusion
> > measurement
> > > =
> >
> > > =3D of fluorescence-labeled amphiphilic molecules with a
> > standard=20
> > > fluorescence microscope. Biophys. J. 72:1701-1710.
> > >
> > > A recent paper describing a FRAP technique using 
> continuous spot=20 
> > > photobleaching allowing to calculate dissociation and residence 
> > > times=20 at binding sites in addition to the diffusion
> > > coefficient:
> > >
> > > 19. Wachsmuth,M.; Weidemann,T.; Muller,G.; Hoffmann-Rohrer,U.W.; 
> > > =3D=20 Knoch,T.A.; Waldeck,W.; Langowski,J. 2003. Analyzing 
> > > intracellular=20 binding and =3D diffusion with continuous 
> > > fluorescence photobleaching. =
> >
> > > Biophys. J. 84:3353-3363.
> > >
> > >
> > >
> > > -----Oorspronkelijk bericht-----
> > > Van: Confocal Microscopy List
> > [mailto:[log in to unmask]] =
> > =3D=20
> > > Namens Narasimham Jammi
> > > Verzonden: woensdag 24 november 2004 0:59
> > > Aan: [log in to unmask]
> > > Onderwerp: FRAP experiments
> > >
> > >
> > > Search the CONFOCAL archive at=20 
> > > http://listserv.acsu.buffalo.edu/cgi-bin/wa?S1=3D3Dconfocal
> > >
> > > Hi all,
> > >  I have a question regarding the number of bleach
> > iterations one would
> > > =
> >
> > > =3D want to use in a typical FRAP experiment. I understand
> > that one=20
> > > would want to minimize the number of bleach iterations
> > (preferrably=20
> > > limit it to 1 =3D bleach at 100% laser intensity) or else
> > fall prey to
> > > =
> >
> > > the 'corona' effect at the ROI, thereby leading to an increase=20
> > > (flawed) in the diffusion =3D coffecients. However, 
> bleaching just =
> > once=20
> > > leads to uneven decrease in fluorescence intensities over 
> different 
> > > samples (for eg, the intensity on ROI goes =3D from 100% 
> to 60% in 
> > > sample 1, sample 2: 100% to70%, sample 3: 100% to 80% =3D
> > etc). Does
> > > this make a difference in interpreting the data?
> > >
> > > thanks
> > > -Jammi
> > >
> >
>