Transcript Slajd 1

PATHS OF MOTION AND VELOCITY DISTRIBUTION FUNCTION
OF LIVING SPERM CELL STUDIED BY OPTICAL METHODS
Anastasiya Derkachova, , Gennadiy Derkachov , Krystyna Kolwas, Agnieszka Sozańska
Institute of Physics, Polish Academy of Sciencies,
Al. Lotników 32/46, 02-668, Warszawa
ABSTRACT
MATERIALS and EXPERIMENTAL SETUP
The method of sperm motility analysis, introduced and developed in our
group [1], is based on a numerical processing of the optical contrast of the
movie images illustrating the dynamics of the sperm cells movement. An
appropriate analysis of a grey scale level of the superimposed images allows
us to access sperm motility. Using the recently improved numerical
processing method, we can investigate both: motion paths and velocities of
single cells. We study the correlation of the reconstructed velocity
distribution function and the measured motility. We observe how these
quantities change in the process of the cells ageing for samples of different
initial biological activity measured by their initial motility.
For semen visualization, we use the microscope with Hoffman modulation
contrast (Nikon Eclipse TS100-F) equipped with a CCD camera. A PC
computer supplied with FireWire card is used to acquire and to analyse
the data. The temperature of the microscope table and of a microscope glass
pool 0.7mm deep, is electronically controlled. The study is made as a
function of temperature for samples of cryopreserved bovine
spermatozoa from Łowicz Semen Storage Centre..
The collection and preparation of sperm cells
The semen from Łowicz Storage Center was
stored in liquid nitrogen. The sperm cell
concentration for each straw was assessed by the
storage center before frizzing. A low sperm
concentration was defined as <10 x 106 sperm/mL, a
medium concentration as between 20 – 40 x 106
sperm/mL, and a high concentration as > 150 x 106
sperm/mL. Sperm counts were performed with use of
a hemacytometer method. Before the experiment
the sperm specimen is warmed in a water bath at
temperature of 37C. A 1:40 dilution of semen was
prepared with PBS (Phosphate Buffer Saline).
The several semen specimens prepared in that
way were than kept at the temperature of 37°C for
different times of incubation (0h1h) to achieve the
specimens of different motility.
[1] A. Sozańska, K. Kolwas, J. Galas, N. Błocki, A. Czyżewski, Simple optical method of qualitative assessment
of sperm motility: preliminary results. Proc. SPIE, 5959 176 (2005)
Experimental setup
Water bath with the thermoregulations system
for thawing and incubation of sperm cells.
CCD camera
Microscope with Hoffman modulation contrast
(Nikon Eclipse TS100-F)
The microscope table was stabilized at 37°C,to unsure the optimal survival
temperature for the bovine spermatozoa under study.
METHODS
The methods we used for image evaluation is based on the numerically
supported phase contrast microscope technique. It allows for cheap and
objective comparison of sperm motility of different sperm samples, as
well for analysis of the sperm cells tracks, and velocities.
The method relies on a numerical processing of the optical contrast of
the sperm images registered as a movie by a CCD camera integrated with
the eyepiece of the microscope with Hoffman modulation contrast
(Nikon Eclipse TS100-F). Every movie was analyzed frame by frame.
The unwanted background is eliminated by standard Matlab function
in several steps:
• assignment of the background level (Fig 1b);
• subtraction of the background from the image. As a result we obtain
the image in grayscale of low intensity values (Fig.1c);
• magnification of the intensity values of the grayscale image (Fig 1d);
• conversion of the grayscale image to the binary image. To the all
illuminated pixels of the grayscale image (Fig 1d) the value 1 (white
color) is assigned. To the all remaining pixels with the value 0 (black
color) is ascribed (Fig.2b) .
Motility detection
Evaluation of the gray scale level for the total area of the
superimposed frames (Fig. 5, right-hand side) in comparison with the
gray scale level for the immobile or drifting sperm cells (Fig 5. on left)
gives us the information about motility of the sperm cells in percents.
Fig. 2 illustrates some sample examples after numerical processing.
a)
b)
Fig. 2. The frame of a movie : (a) before and (b) after numerical processing.
All of the binary images are summarized (Fig. 3 , the left handside). As a result we obtain the binary image (Fig. 3 on the right) and
the underlying data matrix containing information about the
dynamics of the sperm sample (Fig.4).
Fig. 5. The superimposed frames of a movie after numerical processing.
Tracks and velocities detection
a)
c)
Fig. 3. Illustration of the numerical processing of the successive frames of a
movie the final result for the superimposed frames .
b)
d)
Fig. 1. An example frame of a movie: (a) before numerical processing; (b) after assigning the background
level; (c) after subtracting the background from the image and (d) after expanding the intensity
values in a grayscale image.
Fig. 4. The 3D images of the final binary image.
Tracks and velocity detection
procedure is based on evaluation of a
medium intensity along a selected
track. The tracks are hand-marked in
several track-points with help of a
mouse and marked with a bold line.
The velocity of cell along a
selected track is defined from
medium intensity as: V = sVm / I,
where s is a cell size [m], Vm is a
frequency of an image acquisition
[frames/s]; I is a medium intensity
along a track [number of frames].
Fig. 6. Selection of a sperm cell track
allowing the velocity evaluation
from the track intensity.
SUMMARY
RESULTS
In this study we present the modified numerical procedure of for
sperm motility, tracks and velocities assessment. The method is based
on the numerically supported phase contrast technique applied in
analysis of the images of a movie illustrating sperm dynamics. In
comparison with the previous one [1], the new procedure allow us to
analyze not only the motility, but also sperm tracks and velocity
distribution and to consider the drifting die sperm cells.
Fig. 7. Distribution of the tracks frequency versus intensity (left-hand side), and of the
sperm cells velocity (right-hand side) for samples with motility 50% as a
function of time.
Fig. 8. Distribution of the tracks frequency versus intensity (left-hand side), and of the
sperm cells velocity (right-hand side) for samples with motility 56% as a function of
time.
Fig. 9. Temporal evolution of the velocity (left-hand side) and motility (right-hand side)
for samples with the initial sperm motility 50%, 56% and 63% .
We study the correlation of the reconstructed velocity distribution
function and the measured motility.
Our results indicate that in the process of the cells ageing as the
sperm motility decreases, the most probable sperm velocity also
decrease. The correlation between the sperm cells motility and the
sperm probable velocity has not yet been established. The larger
statistics of the results is still needed for the analysis of such
correlation.
Fig. 9. The velocity (left-hand side) and
the motility (right-hand side)
time evolution for samples with
the initial sperm motility 50%,
56% and 63%.
ACKNOWLEDGEMENTS:
We’d like to thank a lot Mrs Grażyna Gasik from Łowicz
Semen Storage Centre for samples supplies.