Keeping house and yard together is a full time job, add to that my total addiction to pieces and puzzles (mosaic, quilts, stained glass, patterns etc)… and my daughter’s house and yard… all of which is falling into ruins… ha ha… but that’s oK, entropy and rebirth are part of life.
I just put my fingers on my new “pause” button, a polymer clay refrigerator magnet, and acknowledge my mortality haha.,… how funny that that piece of refrigerator art makes a difference…. i should be more intellectual and go pray, or meditate, or touch a reliqious mandala, or finger a japa mala, or kiss a talisman, of fondle worry beads…. OK now i have to look up the history of beads…… get this… “The word bead derives from the old Anglo-Saxon word “bede” (prayer). ” ha ha ha ha ha — i would never have guessed.
There is science behind this… amen.
This four month cycle of peaks and valleys for covid infections ought to get someone’s attention. (https://www.worldometers.info/coronavirus/) I sure have not heard anything about “four months”.
I think this image shows pretty nicely how little, except for cosmetics, the image processing of a cropped portion of a multimer involved in immune defense and differentiation in epithelia shows here affects the raw data (LUT grayscale plots). There are small variations in the length of the “arm” which are more likely due to that actual tracing in ImageJ than any difference due to processing. That said, gaussian blur tends to increase the dimensions slightly, highpass filtering increases the grayscale, and unsharp mask creates greater peak heights. So the peak number and the smoothness of the plot can be improved with processing, and the peak height, but no real gain in information is obtained.
The greater task is to look carefully at the molecule, deciding whether tracings of the beginning and ending of close, twisted and overlapping arms (as plotted) (made by hand) make sense.
Images below show plots (color coded as to image processing filters used) and the actual images and trace-lines (screen print from ImageJ tracing). In this case: filters, each named, were performed in photoshop; plots were made in excel as traced in ImageJ; calculator.net was used for determining means and SD of arm length and peak number; corelDRAW was used to normalize the x axis (y axis remained unchanged from original plots) and to color code the plot lines.
Next task is to measure peak widths and heights. Unsharp mask (amount 300, 40px radius, 20 threshold) followed by a 10px gaussian blur provided the smoothest plot. The High peak (left) and low peak height for the next three peaks, and a subsequent high peak seems to be a pretty prevalent pattern for arms in this molecule.
This is the plot for unsharp mask and gaussian blur. It is so remarkably like the very first plots I made on this protein. Since 99.34 nm was close to 100 i used a 100 set of 1 nm dividers to mark out the valleys of these peaks. Interesting features are the absolute regularity of the first five peaks, not in height, but in width, and the first and 4th peaks being higher, and the series of similar size peaks in the middle of the plot.
High pass filtering can help sort out background from data, especially microscopic data. Here is a summary about the high pass filter when used alone, and with gaussian blur. The subject matter is a segment of a multimer (either round or linear) and the brightest peak is where the tracing for gray scale LUT tables begins. Each trace is shown, and along with that a plot of the peak height (and soon to be measured peak width (at mid height and at the base). The plots of the arms shown at the bottom of the figure are color coded with the plots shown in the graph (graph made in image J, highpass filter and gaussian blur made with photoshop 6. Figure assembeled in CorelDRAW x5. THis is NOT surfactant protein A or D, but another multimer involved in innate immunity.
Still at it, not quite half way after one year, but close.
Using CorelDRAW19 various processing algorithms have been applied to one AFM image of surfactant protein D. This image was derived from Arroyo et al, and is among dozens of images from various authors that I am using to test the validity and efficacy of such image processing. The list of programs used for this particular image (then vary from processing programs, e.g. photoshop, gimp, gwiddion, imageJ etc. because of the menu options in each program) and from free and proprietary image processing libraries that may or not be available to software developers. While it has taken months, the comparison is something that I needed to do since I have both old and new versions of the industry standards (CorelPhotoPaint, and Draw, and Photoshop) and it was important to see whether there were changes in image processing algorithms that caused significant differences in gray scale (y axis) for surfactant protein D images.
the list for this composite (plot) overlay is: gaussian blur (5px); gaussian blur (5px) and high pass 40%-10 px radius; gaussian blur (5px) unsharpmask (300%- 20 px radius- threshold 50; lowpass 100% 10 px radius; maximum 50% 10 px radius; median 5 px radius; minimum 50% 10 px radius; smartblur 50. Each of the resulting image were measured using ImageJ. Plots were conformed to the mean arm length of all processing and measuring for this single image. A single background measure (each background was taken at the same time as the measurements, and in the same location) is shown around 50 on the gray scale.
Each plot is a different color and each arm (meaning CRD to CRD in a hexamer) were plotted separately and are shown separately thus, 16 individual plots and 16 colors. Approximate width at the valley of the plots is given in nm.
Peak counts in the span of both hexamers of a dodecamer comes out to be something between an even and an odd number. This is not really interesting except that it might relate to the issue of whether the N termini (junction of four trimer N termini) that is the center and highest peak found with AFM of surfactant protein d dodecamers…. there is good visual data that says sometimes the N termini are joined in ways other than overlapping (overlapping is the wrong word, more like juxtaposed). The later, in AFM can be side by side, or end to end. No consensus has been found in the literature so far by me, by me anyway. I subscribe to the idea that more configurational variations happen that is usually realized.
Just over 350 measurements of brightness”peaks” for ONE molecule of SP-D (a dodecamer AFM image from arroyo et al (which i have named 41 aka 45) the data for peaks along the arms is: (keep in mind that the center peak is likely not mirrored in a consistent way, thus the number of paired peaks on right and left arms of both hexamers will tend to be an odd number) in that sense, the peaks from looking quickly at each image, and then using ImageJ to plot the peaks of brightness, and adding those, the number of peaks in each hexamer is as follows. This particular molecule has arms of different lengths with what I have called “arm 2” being longer than arm 1. The right portion of the dodecamer looking like it was been stretched during preparation. It is still useful to see whether the physical elongation of an SP-D arm allows for greater, or lesser definition of the peaks which occur in the area between the N termini and respective CRD domains.
Below, the image, the summary statistics. These are all measures on the same image, processed in a dozen different image processing programs. The image below is a sample, bar marker is green, and 100nm. Image stated above is from arroyo et al.
There are some differences in the “libraries” that are used for image processing. It is important to determine which is best for your application. Below is a quick visual summary of 5 and 10 px gaussian blurs from a dozen or so programs. Inkscape is missing, as I could not find the specific term “gaussian” for any blur filters. Most of these programs are similar but some are expensive to purchase, or have a monthly contract for, others are free software. While i really do like photoshop (two versions here) and corelDRAW and corelPhotopaint (two versions here), ImageJ is easy to use and provides pretty comparable results albeit on a very much smaller selection of effects and filters to the former programs. The bar marker example here was a vector box (no outline) layered onto an image, exported as a tif and processed in these programs as such.